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International Center for Computational Logic - Benutzerbeiträge [de]
2024-03-28T20:54:29Z
Benutzerbeiträge
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https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=38394
Advanced Problem Solving and Search (SS2023)
2023-06-19T09:25:05Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Constraint Satisfaction Problems<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Answer Set Programming<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. We invite you to use the forum to ask questions and share your exercise solutions.<br />
<br />
Please, register for the course on the OPAL site:<br />
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/39148716041<br />
<br />
===Exam===<br />
Key information:<br />
There are two forms of examination:<br />
<br />
Students of the CMS master and exchange students: <br />
*The written exam will take place on the 28th of July, 2023 at the TU Dresden campus. There is no possibility to take the exam remotely.<br />
*You must register in Selma or with your examination office. In the future, you will also need to register on the OpalExam platform. A link will be provided for this.<br />
<br />
Students with complex examinations:<br />
*Please, schedule your oral exams with Ramona Behling (ramona.behling@tu-dresden.de).<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=HSZ/0401<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=HSZ/0401<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E009<br />
|Date=2023/04/28<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/08<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=HSZ/0401<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E009<br />
|Date=2023/05/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=HSZ/0401<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=HSZ/0401<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=HSZ/0401<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (Local Search)<br />
|Room=APB E009<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=HSZ/0401<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Tabu Search)<br />
|Room=APB E009<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=HSZ/0401<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E009<br />
|Date=2023/06/23<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=HSZ/0401<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E009<br />
|Date=2023/06/30<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=HSZ/0401<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E009<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=HSZ/0401<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=HSZ/0401<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=38393
Advanced Problem Solving and Search (SS2023)
2023-06-19T09:20:32Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Constraint Satisfaction Problems<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Answer Set Programming<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. We invite you to use the forum to ask questions and share your exercise solutions.<br />
<br />
Please, register for the course on the OPAL site:<br />
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/39148716041<br />
<br />
===Exam===<br />
Key information:<br />
There are two forms of examination:<br />
<br />
Students of the CMS master: <br />
*The written exam will take place on the 28th of July, 2023 at the TU Dresden campus. There is no possibility to take the exam remotely.<br />
*You must register in Selma. In the future, you will also need to register on the OpalExam platform. A link will be provided for this.<br />
<br />
Students with complex examinations and exchange students:<br />
*Please, schedule your oral exams with Ramona Behling (ramona.behling@tu-dresden.de).<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=HSZ/0401<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=HSZ/0401<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E009<br />
|Date=2023/04/28<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/08<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=HSZ/0401<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E009<br />
|Date=2023/05/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=HSZ/0401<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=HSZ/0401<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=HSZ/0401<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (Local Search)<br />
|Room=APB E009<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=HSZ/0401<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Tabu Search)<br />
|Room=APB E009<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=HSZ/0401<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E009<br />
|Date=2023/06/23<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=HSZ/0401<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E009<br />
|Date=2023/06/30<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=HSZ/0401<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E009<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=HSZ/0401<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=HSZ/0401<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=38392
Advanced Problem Solving and Search (SS2023)
2023-06-19T09:19:49Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Constraint Satisfaction Problems<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Answer Set Programming<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. We invite you to use the forum to ask questions and share your exercise solutions.<br />
<br />
Please, register for the course on the OPAL site:<br />
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/39148716041<br />
<br />
===Exam===<br />
Key information:<br />
There are two forms of examination:<br />
<br />
Students of the CMS master: <br />
-The written exam will take place on the 28th of July, 2023 at the TU Dresden campus. There is no possibility to take the exam remotely.<br />
-You must register in Selma. In the future, you will also need to register on the OpalExam platform. A link will be provided for this.<br />
<br />
Students with complex examinations and exchange students:<br />
-Please, schedule your oral exams with Ramona Behling (ramona.behling@tu-dresden.de).<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=HSZ/0401<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=HSZ/0401<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E009<br />
|Date=2023/04/28<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/08<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=HSZ/0401<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E009<br />
|Date=2023/05/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=HSZ/0401<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=HSZ/0401<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=HSZ/0401<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (Local Search)<br />
|Room=APB E009<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=HSZ/0401<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Tabu Search)<br />
|Room=APB E009<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=HSZ/0401<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E009<br />
|Date=2023/06/23<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=HSZ/0401<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E009<br />
|Date=2023/06/30<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=HSZ/0401<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E009<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=HSZ/0401<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=HSZ/0401<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3349&diff=38196
Inproceedings3349
2023-05-20T09:35:05Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Lucía<br />
|ErsterAutorNachname=Gómez Álvarez<br />
|FurtherAuthors=Hannes Straß; Sebastian Rudolph<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=Tractable Diversity: Scalable Multiperspective Ontology Management via Standpoint EL<br />
|To appear=1<br />
|Year=2023<br />
|Booktitle=Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023<br />
}}<br />
{{Publikation Details<br />
|Download=First order standpoint logic.pdf<br />
|Projekt=KIMEDS, ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Datei:First_order_standpoint_logic.pdf&diff=38195
Datei:First order standpoint logic.pdf
2023-05-20T09:35:01Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div></div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3350&diff=38194
Inproceedings3350
2023-05-20T09:33:30Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Brandon<br />
|ErsterAutorNachname=Bennett<br />
|FurtherAuthors=Lucía Gómez Álvarez<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=Vagueness in Predicates and Objects<br />
|To appear=1<br />
|Year=2023<br />
|Booktitle=Proceedings of the 13th International Conference on Formal Ontology in Information Systems, FOIS 2023<br />
}}<br />
{{Publikation Details<br />
|Download=FOIS 2023 BB LGA Revised.pdf<br />
|Projekt=ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Datei:FOIS_2023_BB_LGA_Revised.pdf&diff=38193
Datei:FOIS 2023 BB LGA Revised.pdf
2023-05-20T09:33:26Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div></div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3352/en&diff=38192
Inproceedings3352/en
2023-05-20T09:28:41Z
<p>Lucía Gómez Álvarez: Page created automatically by parser function on page Inproceedings3352</p>
<hr />
<div>#REDIRECT [[Inproceedings3352]]</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3352&diff=38191
Inproceedings3352
2023-05-20T09:28:40Z
<p>Lucía Gómez Álvarez: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Lucía |ErsterAutorNachname=Gómez Álvarez |FurtherAuthors=Sebastian Rudolph; Hannes Straß }} {{Inproceedings…“</p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Lucía<br />
|ErsterAutorNachname=Gómez Álvarez<br />
|FurtherAuthors=Sebastian Rudolph; Hannes Straß<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=Pushing the Boundaries of Tractable Multiperspective Reasoning: A Deduction Calculus for Standpoint EL+<br />
|To appear=1<br />
|Year=2023<br />
|Booktitle=Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning<br />
|Publisher=IJCAI Inc<br />
}}<br />
{{Publikation Details<br />
|Download=2304.14323.pdf<br />
|Projekt=ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Datei:2304.14323.pdf&diff=38190
Datei:2304.14323.pdf
2023-05-20T09:28:20Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div></div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3351/en&diff=38189
Inproceedings3351/en
2023-05-20T09:23:45Z
<p>Lucía Gómez Álvarez: Page created automatically by parser function on page Inproceedings3351</p>
<hr />
<div>#REDIRECT [[Inproceedings3351]]</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3351&diff=38188
Inproceedings3351
2023-05-20T09:23:44Z
<p>Lucía Gómez Álvarez: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Nicola |ErsterAutorNachname=Gigante |FurtherAuthors=Lucía Gómez Álvarez; Tim Lyon }} {{Inproceedings |Referie…“</p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Nicola<br />
|ErsterAutorNachname=Gigante<br />
|FurtherAuthors=Lucía Gómez Álvarez; Tim Lyon<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=Standpoint Linear Temporal Logic<br />
|To appear=1<br />
|Year=2023<br />
|Booktitle=Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning<br />
|Publisher=IJCAI Inc<br />
}}<br />
{{Publikation Details<br />
|Download=2304.14243.pdf<br />
|Projekt=ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Datei:2304.14243.pdf&diff=38187
Datei:2304.14243.pdf
2023-05-20T09:23:38Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div></div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3325&diff=38173
Inproceedings3325
2023-05-16T11:10:18Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Lucía<br />
|ErsterAutorNachname=Gómez Álvarez<br />
|FurtherAuthors=Sebastian Rudolph; Hannes Straß<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=Modelling Multiple Perspectives by Standpoint-Enhanced Description Logics (Extended Abstract)<br />
|To appear=0<br />
|Year=2022<br />
|Month=August<br />
|Booktitle=Proceedings of the 35th International Workshop on Description Logics (DL 2022)<br />
|Publisher=CEUR Workshop Proceedings<br />
|Editor=Ofer Arieli, Martin Homola, Jean Christoph Jung, Marie-Laure Mugnier<br />
|Volume=3263<br />
}}<br />
{{Publikation Details<br />
|Abstract=The importance of taking individual, potentially conflicting perspectives into account when dealing with knowledge has been widely recognised. Many existing ontology management approaches fully merge knowledge perspectives, which may require weakening in order to maintain consistency; others represent the distinct views in an entirely detached way. As an alternative, we propose Standpoint Logic, a simple, yet versatile generic approach to extend existing KR formalisms by the capability to express domain knowledge relative to diverse, possibly conflicting standpoints, which can be hierarchically organised, combined, and put in relation with each other. As a concrete showcase, this extended abstract introduces the standpoint-enhanced version of the very expressive description logic SROIQbs, which is tightly connected to the W3C-standardised ontology language OWL 2 DL. We report that, by virtue of a “small model property” and using some elaborate encoding tricks, it is possible to establish a polytime translation from standpoint-enhanced SROIQbs into plain SROIQbs. By virtue of this result, existing highly optimised OWL reasoners can be used off the shelf to provide practical reasoning support for ontology languages from the OWL family extended by standpoint modelling.<br />
|Download=DL22-16.pdf<br />
|Projekt=DeciGUT, ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}<br />
{{Forschungsgebiet Auswahl<br />
|Forschungsgebiet=Beschreibungslogiken<br />
}}<br />
{{Forschungsgebiet Auswahl<br />
|Forschungsgebiet=Wissensrepräsentation und logisches Schließen<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3350/en&diff=38172
Inproceedings3350/en
2023-05-16T11:09:25Z
<p>Lucía Gómez Álvarez: Page created automatically by parser function on page Inproceedings3350</p>
<hr />
<div>#REDIRECT [[Inproceedings3350]]</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3350&diff=38171
Inproceedings3350
2023-05-16T11:09:25Z
<p>Lucía Gómez Álvarez: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Brandon |ErsterAutorNachname=Bennett |FurtherAuthors=Lucía Gómez Álvarez }} {{Inproceedings |Referiert=1 |Tit…“</p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Brandon<br />
|ErsterAutorNachname=Bennett<br />
|FurtherAuthors=Lucía Gómez Álvarez<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=Vagueness in Predicates and Objects<br />
|To appear=1<br />
|Year=2023<br />
|Booktitle=Proceedings of the 13th International Conference on Formal Ontology in Information Systems, FOIS 2023<br />
}}<br />
{{Publikation Details<br />
|Projekt=ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3349/en&diff=38170
Inproceedings3349/en
2023-05-16T11:07:25Z
<p>Lucía Gómez Álvarez: Page created automatically by parser function on page Inproceedings3349</p>
<hr />
<div>#REDIRECT [[Inproceedings3349]]</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3349&diff=38169
Inproceedings3349
2023-05-16T11:07:24Z
<p>Lucía Gómez Álvarez: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Lucía |ErsterAutorNachname=Gómez Álvarez |FurtherAuthors=Hannes Straß; Sebastian Rudolph }} {{Inproceedings…“</p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Lucía<br />
|ErsterAutorNachname=Gómez Álvarez<br />
|FurtherAuthors=Hannes Straß; Sebastian Rudolph<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=Tractable Diversity: Scalable Multiperspective Ontology Management via Standpoint EL<br />
|To appear=1<br />
|Year=2023<br />
|Booktitle=Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023<br />
}}<br />
{{Publikation Details<br />
|Projekt=KIMEDS, ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37906
Advanced Problem Solving and Search (SS2023)
2023-03-16T17:25:43Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Constraint Satisfaction Problems<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Answer Set Programming<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. We invite you to use the forum to ask questions and share your exercise solutions.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/23<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/30<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37905
Advanced Problem Solving and Search (SS2023)
2023-03-16T17:24:36Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Constraint Satisfaction Problems<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Answer Set Programming<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. We invite you to use the forum to ask questions and share your exercise solutions.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (ASP)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/23<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/30<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37880
Advanced Problem Solving and Search (SS2023)
2023-02-28T23:00:33Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Constraint Satisfaction Problems<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Answer Set Programming<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. We invite you to use the forum to ask questions and share your exercise solutions.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/05<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/05/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/30<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37879
Advanced Problem Solving and Search (SS2023)
2023-02-28T17:41:17Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/05<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/05/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/30<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37878
Advanced Problem Solving and Search (SS2023)
2023-02-28T17:38:42Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/05<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/30<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37877
Advanced Problem Solving and Search (SS2023)
2023-02-28T17:26:25Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/26<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/05<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/23<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/14<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37876
Advanced Problem Solving and Search (SS2023)
2023-02-28T17:22:19Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/26<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/23<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/07<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/14<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37875
Advanced Problem Solving and Search (SS2023)
2023-02-28T17:20:29Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/26<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/05/16<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/23<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/05/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/07/07<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/07/14<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/07/10<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/17<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37874
Advanced Problem Solving and Search (SS2023)
2023-02-28T17:17:17Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/26<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/09<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/05/16<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/05/29<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/02<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/05/29<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/06/30<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37873
Advanced Problem Solving and Search (SS2023)
2023-02-28T13:27:10Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/05/01<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/05/12<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/08<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/19<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/05/15<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/05/26<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=virtual<br />
|Date=2023/05/22<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/05/29<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (ASP 2)<br />
|Room=APB E005<br />
|Date=2023/06/02<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/05/29<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/06/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (CSP)<br />
|Room=APB E005<br />
|Date=2023/06/16<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/06/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (EA)<br />
|Room=APB E005<br />
|Date=2023/06/23<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=virtual<br />
|Date=2023/06/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/06/30<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/06/26<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/03<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37872
Advanced Problem Solving and Search (SS2023)
2023-02-28T13:17:12Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session.<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/04<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/11<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/04/25<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/04/25<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/04/25<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/02<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/02<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2 (Tabu Search)<br />
|Room=APB E005<br />
|Date=2023/05/02<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=virtual<br />
|Date=2023/05/09<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/05/09<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (ASP 1)<br />
|Room=APB E005<br />
|Date=2023/05/09<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
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|Date=2023/05/16<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
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|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
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}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=virtual<br />
|Date=2023/05/23<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=virtual<br />
|Date=2023/05/30<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (CSP)<br />
|Room=APB E005<br />
|Date=2023/05/30<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (CSP)<br />
|Room=APB E005<br />
|Date=2023/05/30<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=virtual<br />
|Date=2023/06/13<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
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|Date=2023/06/13<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
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|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
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|Date=2023/06/20<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
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}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
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|Date=2023/06/27<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
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|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
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}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)/en&diff=37871
Advanced Problem Solving and Search (SS2023)/en
2023-02-28T13:15:40Z
<p>Lucía Gómez Álvarez: Page created automatically by parser function on page Advanced Problem Solving and Search (SS2023)</p>
<hr />
<div>{{Vorlesung/en}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(SS2023)&diff=37870
Advanced Problem Solving and Search (SS2023)
2023-02-28T13:15:40Z
<p>Lucía Gómez Álvarez: Die Seite wurde neu angelegt: „{{Vorlesung |Title=Advanced Problem Solving and Search |Research group=Computational Logic |Lecturers=Lucía Gómez Álvarez, Sarah Alice Gaggl |Tutors=Lucía…“</p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez, Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez, Sarah Alice Gaggl<br />
|Term=SS<br />
|Year=2023<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Answer Set Programming<br />
*Constraint Satisfaction<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of the former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. <br />
<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=virtual<br />
|Date=2023/04/04<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=virtual<br />
|Date=2023/04/11<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=virtual<br />
|Date=2023/04/25<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (Local Search)<br />
|Room=APB E005<br />
|Date=2023/04/25<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
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|Room=APB E005<br />
|Date=2023/04/25<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=virtual<br />
|Date=2023/05/02<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
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|Room=APB E005<br />
|Date=2023/05/02<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
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|Date=2023/05/02<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
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}}<br />
{{Vorlesung Zeiten<br />
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|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
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}}<br />
{{Vorlesung Zeiten<br />
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|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
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|Date=2023/06/13<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
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}}<br />
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}}<br />
{{Vorlesung Zeiten<br />
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}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
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|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E005<br />
|Date=2023/06/20<br />
|DS=DS3<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=virtual<br />
|Date=2023/06/27<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 8 (Q&A)<br />
|Room=APB E005<br />
|Date=2023/06/27<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=virtual<br />
|Date=2023/07/04<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Luc%C3%ADa_G%C3%B3mez_%C3%81lvarez&diff=37866
Lucía Gómez Álvarez
2023-02-26T13:33:04Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Mitarbeiter<br />
|Vorname=Lucía<br />
|Nachname=Gómez Álvarez<br />
|Akademischer Titel=Dr.<br />
|Forschungsgruppe=Computational Logic<br />
|Stellung=Wissenschaftliche Mitarbeiterin<br />
|Ehemaliger=0<br />
|Email=lucia.gomez_alvarez@tu-dresden.de<br />
|Raum=APB 2033<br />
|Bild=Lucia400x600.jpg<br />
|Info=Since April 2020, I am a postdoctoral research assistant at the Computational Logic Group at the Technische Universität Dresden. <br />
<br><br />
My research interests are in the area of Knowledge Representation and Reasoning. I am particularly (but not exclusively) interested in the representation of concepts and of semantically variable languages, and I look at theoretical issues (linguistic and philosophical), at representational frameworks (mostly logic-based) and at applications. <br />
<br><br />
Before joining the TU Dresden I was awarded the degree of PhD in Computer Science in March 2020 at the University of Leeds, where I was working under the supervision of Brandon Bennett.<br />
|Info EN=Since April 2020, I am a postdoctoral research assistant at the Computational Logic Group at the Technische Universität Dresden. <br />
<br><br />
My research interests are in the area of Knowledge Representation and Reasoning. I am particularly (but not exclusively) interested in the representation of concepts and of semantically variable languages, and I look at theoretical issues (linguistic and philosophical), at representational frameworks (mostly logic-based) and at applications. <br />
<br><br />
Before joining the TU Dresden I was awarded the degree of PhD in Computer Science in February 2020 at the University of Leeds, where I was working under the supervision of Brandon Bennett.<br />
|DBLP=https://dblp.org/pid/182/7478.html<br />
|Google Scholar=https://scholar.google.com/citations?user=KDEgIXsAAAAJ&hl=en<br />
|Publikationen anzeigen=1<br />
|Abschlussarbeiten anzeigen=1<br />
}}<br />
{{Forschungsgebiet Auswahl<br />
|Forschungsgebiet=Wissensrepräsentation und logisches Schließen<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Luc%C3%ADa_G%C3%B3mez_%C3%81lvarez&diff=37865
Lucía Gómez Álvarez
2023-02-26T13:30:43Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Mitarbeiter<br />
|Vorname=Lucía<br />
|Nachname=Gómez Álvarez<br />
|Akademischer Titel=Dr.<br />
|Forschungsgruppe=Computational Logic<br />
|Stellung=Wissenschaftliche Mitarbeiterin<br />
|Ehemaliger=0<br />
|Email=lucia.gomez_alvarez@tu-dresden.de<br />
|Raum=APB 2033<br />
|Bild=Lucia400x600.jpg<br />
|Info=Since April 2020, I am a postdoctoral research assistant at the Computational Logic Group at the Technische Universität Dresden. <br />
<br><br />
My research interests are in the area of Knowledge Representation and Reasoning. I am particularly (but not exclusively) interested in the representation of concepts and of semantically variable languages, and I look at theoretical issues (linguistic and philosophical), at representational frameworks (mostly logic-based) and at applications. <br />
<br><br />
Before joining the TU Dresden I was awarded the degree of PhD in Computer Science in March 2020 at the University of Leeds, where I was working under the supervision of Brandon Bennett.<br />
|Info EN=Since April 2020, I am a postdoctoral research assistant at the Computational Logic Group at the Technische Universität Dresden. <br />
<br><br />
My research interests are in the area of Knowledge Representation and Reasoning. I am particularly (but not exclusively) interested in the representation of concepts and of semantically variable languages, and I look at theoretical issues (linguistic and philosophical), at representational frameworks (mostly logic-based) and at applications. <br />
<br><br />
Before joining the TU Dresden I was awarded the degree of PhD in Computer Science in February 2020 at the University of Leeds, where I was working under the supervision of Brandon Bennett.<br />
|DBLP=https://dblp.org/db/conf/dlog/dlog2022.html#AlvarezRS22<br />
|Google Scholar=https://scholar.google.com/citations?user=KDEgIXsAAAAJ&hl=en<br />
|Publikationen anzeigen=1<br />
|Abschlussarbeiten anzeigen=1<br />
}}<br />
{{Forschungsgebiet Auswahl<br />
|Forschungsgebiet=Wissensrepräsentation und logisches Schließen<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3325&diff=37864
Inproceedings3325
2023-02-26T13:21:05Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Lucía<br />
|ErsterAutorNachname=Gómez Álvarez<br />
|FurtherAuthors=Sebastian Rudolph; Hannes Straß<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=Modelling Multiple Perspectives by Standpoint-Enhanced Description Logics (Extended Abstract)<br />
|To appear=1<br />
|Year=2022<br />
|Month=August<br />
|Booktitle=Proceedings of the 35th International Workshop on Description Logics (DL 2022)<br />
|Publisher=CEUR Workshop Proceedings<br />
|Editor=Ofer Arieli, Martin Homola, Jean Christoph Jung, Marie-Laure Mugnier<br />
|Volume=3263<br />
}}<br />
{{Publikation Details<br />
|Abstract=The importance of taking individual, potentially conflicting perspectives into account when dealing with knowledge has been widely recognised. Many existing ontology management approaches fully merge knowledge perspectives, which may require weakening in order to maintain consistency; others represent the distinct views in an entirely detached way. As an alternative, we propose Standpoint Logic, a simple, yet versatile generic approach to extend existing KR formalisms by the capability to express domain knowledge relative to diverse, possibly conflicting standpoints, which can be hierarchically organised, combined, and put in relation with each other. As a concrete showcase, this extended abstract introduces the standpoint-enhanced version of the very expressive description logic SROIQbs, which is tightly connected to the W3C-standardised ontology language OWL 2 DL. We report that, by virtue of a “small model property” and using some elaborate encoding tricks, it is possible to establish a polytime translation from standpoint-enhanced SROIQbs into plain SROIQbs. By virtue of this result, existing highly optimised OWL reasoners can be used off the shelf to provide practical reasoning support for ontology languages from the OWL family extended by standpoint modelling.<br />
|Download=DL22-16.pdf<br />
|Projekt=DeciGUT, ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}<br />
{{Forschungsgebiet Auswahl<br />
|Forschungsgebiet=Beschreibungslogiken<br />
}}<br />
{{Forschungsgebiet Auswahl<br />
|Forschungsgebiet=Wissensrepräsentation und logisches Schließen<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3339&diff=37863
Inproceedings3339
2023-02-26T13:16:02Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Lucía<br />
|ErsterAutorNachname=Gómez Álvarez<br />
|FurtherAuthors=Sebastian Rudolph; Hannes Straß<br />
}}<br />
{{Inproceedings<br />
|Referiert=1<br />
|Title=How to Agree to Disagree: Managing Ontological Perspectives using Standpoint Logic<br />
|To appear=0<br />
|Year=2022<br />
|Month=Oktober<br />
|Booktitle=Proceedings of the 21st International Semantic Web Conference (ISWC 22)<br />
|Publisher=Springer<br />
|Editor=Ulrike Sattler, Aidan Hogan, Maria Keet, Valentina Presutti, João Paulo A. Almeida, Hideaki Takeda, Pierre Monnin, Giuseppe Pirrò, Claudia d'Amato<br />
|Series=Lecture Notes in Computer Science<br />
|Volume=13489<br />
}}<br />
{{Publikation Details<br />
|Download=ISWC22-98.pdf<br />
|Projekt=DeciGUT, ScaDS.AI<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Article3089&diff=37862
Article3089
2023-02-26T13:14:25Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Adam<br />
|ErsterAutorNachname=Richard-Bollans<br />
|FurtherAuthors=Anthony Cohn; Lucía Gómez Álvarez<br />
}}<br />
{{Article<br />
|Referiert=0<br />
|Title=Identifying and Modelling Polysemous Senses of Spatial Prepositions in Referring Expressions<br />
|To appear=0<br />
|Year=2023<br />
|Journal=Cognitive Systems Research<br />
|Volume=77<br />
|Pages=45-61<br />
}}<br />
{{Publikation Details<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Proceedings3021/en&diff=37861
Proceedings3021/en
2023-02-26T13:11:45Z
<p>Lucía Gómez Álvarez: Page created automatically by parser function on page Proceedings3021</p>
<hr />
<div>#REDIRECT [[Proceedings3021]]</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Proceedings3021&diff=37860
Proceedings3021
2023-02-26T13:11:45Z
<p>Lucía Gómez Álvarez: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Tiago |ErsterAutorNachname=Prince Sales, Maria M. Hedblom, He Tan, Guendalina Righetti, Oliver Kutz, Martin Glau…“</p>
<hr />
<div>{{Publikation Erster Autor<br />
|ErsterAutorVorname=Tiago<br />
|ErsterAutorNachname=Prince Sales, Maria M. Hedblom, He Tan, Guendalina Righetti, Oliver Kutz, Martin Glauer, Janna Hastings, Till Mossakowski, Fabian Neuhaus, Rafael Peñaloza, Srdjan Vesic, Claudenir Morais Fonseca, Jona Thai, Stefano Borgo, Damion M. Dooley, Rhiannon Cameron, Lauren E. Chan, Duccio Cavalieri, Robert Warren, Hande Küçük-McGinty, Matthew Lange, Fernanda Forea, Francesco Vitali, Bart Gajderowicz, Daniela Rosu, Aldo Gangemi, Robert Porzel, Daniel Beßler, Mihai Pomarlan, Mohammed Diab, Alberto Olivares Alarcos<br />
|FurtherAuthors=Lucía Gómez Álvarez<br />
}}<br />
{{Proceedings<br />
|Title=Proceedings of the Joint Ontology Workshops 2022 Episode VIII: The Svear Sommar of Ontology, Jönköping, Sweden.<br />
|To appear=0<br />
|Year=2022<br />
|Publisher=CEUR Workshop Proceedings<br />
|Volume=3249<br />
}}<br />
{{Publikation Details<br />
|Forschungsgruppe=Computational Logic<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(WS2223)/&diff=37531
Advanced Problem Solving and Search (WS2223)/
2022-11-11T14:23:36Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=WS<br />
|Year=2022<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Constraint Satisfaction Problems<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Answer Set Programming<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. We invite you to use the forum to ask questions and share your exercise solutions. <br />
<br />
Please, register for the course on the OPAL site:<br />
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/36566368264/<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Introduction<br />
|Room=SCH/0A01/H<br />
|Date=2022/10/17<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Informed vs. Uninformed Search<br />
|Room=SCH/0A01/H<br />
|Date=2022/10/24<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 1 (A*, Dynamic Programming)<br />
|Room=APB E023<br />
|Date=2022/11/07<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Local Search<br />
|Room=SCH/0A01/H<br />
|Date=2022/11/07<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2.1 (Local Search)<br />
|Room=APB E023<br />
|Date=2022/11/14<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Tabu Search<br />
|Room=SCH/0A01/H<br />
|Date=2022/11/14<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 2.2 (Tabu Search)<br />
|Room=APB E023<br />
|Date=2022/11/21<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Evolutionary Algorithms<br />
|Room=SCH/0A01/H<br />
|Date=2022/11/21<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 3 (EA)<br />
|Room=APB E023<br />
|Date=2022/11/28<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=CSP<br />
|Room=SCH/0A01/H<br />
|Date=2022/11/28<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 4 (CSP)<br />
|Room=APB E023<br />
|Date=2022/12/05<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 1<br />
|Room=SCH/0A01/H<br />
|Date=2022/12/05<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 5 (ASP 1)<br />
|Room=APB E023<br />
|Date=2022/12/12<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 2<br />
|Room=SCH/0A01/H<br />
|Date=2022/12/12<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 6 (ASP 2)<br />
|Room=APB E023<br />
|Date=2022/12/19<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=ASP 3<br />
|Room=SCH/0A01/H<br />
|Date=2022/12/19<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 1<br />
|Room=SCH/0A01/H<br />
|Date=2023/01/09<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 7 (Structural Decompositions)<br />
|Room=APB E023<br />
|Date=2023/01/16<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Structural Decompositions 2<br />
|Room=SCH/0A01/H<br />
|Date=2023/01/16<br />
|DS=DS2<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Übung<br />
|Title=Tutorial 8 (Q&A)<br />
|Room=APB E023<br />
|Date=2023/01/23<br />
|DS=DS1<br />
}}<br />
{{Vorlesung Zeiten<br />
|Lehrveranstaltungstype=Vorlesung<br />
|Title=Q&A<br />
|Room=SCH/0A01/H<br />
|Date=2023/01/23<br />
|DS=DS2<br />
}}</div>
Lucía Gómez Álvarez
https://iccl.inf.tu-dresden.de/w/index.php?title=Advanced_Problem_Solving_and_Search_(WS2223)/&diff=37216
Advanced Problem Solving and Search (WS2223)/
2022-10-02T19:05:03Z
<p>Lucía Gómez Álvarez: </p>
<hr />
<div>{{Vorlesung<br />
|Title=Advanced Problem Solving and Search<br />
|Research group=Computational Logic<br />
|Lecturers=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Tutors=Lucía Gómez Álvarez; Sarah Alice Gaggl<br />
|Term=WS<br />
|Year=2022<br />
|Module=INF-BAS2, INF-VERT2, MCL-KR, MCL-PI, MCL-AI, CMS-COR-FAI<br />
|SWSLecture=2<br />
|SWSExercise=2<br />
|SWSPractical=0<br />
|Exam type=Klausur, mündliche Prüfung<br />
|Description=Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.<br />
<br />
The course covers the following '''topics''':<br />
*Basic Concepts<br />
*Uninformed vs Informed Search<br />
*Local Search, Stochastic Hill Climbing, Simulated Annealing<br />
*Tabu Search<br />
*Constraint Satisfaction Problems<br />
*Evolutionary Algorithms, Genetic Algorithms<br />
*Answer Set Programming<br />
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)<br />
<br />
The course does not cover topics in the area of Machine Learning and Neural Networks.<br />
<br />
NOTE: This course was previously named Problem Solving and Search in Artificial Intelligence. The contents of former PSSAI and APSS are identical, and therefore students can only take one of the two courses.<br />
<br />
===Learning Outcomes===<br />
*The students should identify why typical AI problems are difficult to solve<br />
*The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate <br />
*The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem<br />
*In the tutorials, the students will analyze different problems and develop solutions for them. <br />
<br />
===Prerequisites===<br />
*Basic knowledge of theoretical computer science and Logic. <br />
*Good English skills: both the teaching and examination will be exclusively in English.<br />
<br />
===Organisation===<br />
The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.<br />
<br />
The slides of the lectures and exercises of the tutorials will be uploaded in OPAL, for each corresponding session. We invite you to use the forum to ask questions and share your exercise solutions. <br />
<br />
Please, register for the course on the OPAL site:<br />
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/36566368264/<br />
|Literature=*Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.<br />
*Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.<br />
*Martin Gebser, Benjamin Kaufmann Roland Kaminski, and Torsten Schaub. "Answer Set Solving in Practice". Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan and Claypool Publishers, 2012.<br />
*Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.<br />
*A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.<br />
*Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.<br />
*Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.<br />
*Georg Gottlob, Nicola Leone, and Francesco Scarcello. "Hypertree decompositions and tractable queries", Journal of Computer and System Sciences, 64(3):579–627, 2002. ISSN 0022-0000.<br />
*Artan Dermaku, Tobias Ganzow, Georg Gottlob, Ben McMahan, Nysret Musliu, and Marko Samer. "Heuristic methods for hypertree decomposition", In Alexander Gelbukh and Eduardo F. Morales, editors, MICAI 2008: Advances in Artificial Intelligence, volume 5317 of LNCS, pages 1–11. Springer Berlin Heidelberg, 2008. ISBN 978-3-540-88635-8.<br />
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https://iccl.inf.tu-dresden.de/w/index.php?title=Inproceedings3273&diff=37194
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https://iccl.inf.tu-dresden.de/w/index.php?title=Datei:2020.splu-1.5.pdf&diff=37193
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Lucía Gómez Álvarez