Problem Solving and Search in Artificial Intelligence

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Problem Solving and Search in Artificial Intelligence

Lehrveranstaltung mit SWS 2/2/0 (Vorlesung/Übung/Praktikum) in WS 2020

Dozent

Tutor

Umfang (SWS)

  • 2/2/0

Module

Leistungskontrolle

  • Mündliche Prüfung


Problem solving and search is a central topic in Artificial Intelligence. This course presents several techniques to solve in general difficult problems.

The course covers the following topics:

  • Basic Concepts
  • Uninformed vs Informed Search
  • Local Search, Stochastic Hill Climbing, Simulated Annealing
  • Tabu Search
  • Answer Set Programming
  • Constraint Satisfaction
  • Evolutionary Algorithms, Genetic Algorithms
  • Structural Decomposition Techniques (Tree/Hypertree Decompositions)


Learning Outcomes

  • The students should identify why typical AI problems are difficult to solve
  • The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate
  • 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
  • In the practical part, the students will analyze a given problem and develop a solution for it.

Prerequisites

Basic knowledge of theoretical computer science and Logic. In addition, the course and examination will be exclusively in English.

Organisation

The goals can be acquired by studying the lecture material and solving the exercises of the tutorials.

The lectures will be held on Fridays DS1 (07.30 - 09.00 am) and the tutorials on Fridays DS2 (09.20 - 10.50). Please check the schedule for changes.

Announcement: because of the COVID-19 pandemic we will provide the materials for self-learning on the planned dates for lectures and we will have on-line live sessions for the tutorials.

Please, register for the course on the OPAL site: https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/26346913795/CourseNode/101501861298687

Examination

This year, due to the exceptional COVID-19 pandemic and the high number of registered students, the exam will be written and online, on the OPAL-ONYX platform. It will mostly consist of single and multiple-choice questions as well as some quick exercises.

The exam has finally been scheduled for 11/02/2021 at 16:40h. In addition, a test exam will be carried out on 8/02/2021 at 10:00. It is your responsibility to attend the test exam to ensure that the exam infrastructure works correctly in the equipment that you will use for your exam on the 11th. Of course, no grading will be done on the test exam whatsoever (in fact you will have mock questions). 

As a consequence, regarding complex examinations held jointly with another examiner: - Students who wish to take a complex examination jointly with another examiner need to look for the main examiner. Due to the large number of registered students in PSSAI, I kindly request you to find another main examiner, and I will decide on an individual basis whenever the load is reasonable.  - In principle, PSSAI will only offer separate partial examinations (Teilprüfungen) this semester.

If you wish to register for examination this semester, you must do this via the Examination Office. 

In addition, as previously stated earlier this semester, PSSAI will be offered again in the coming summer semester of 2021. Consequently, examination will be possible again at the end of the summer semester and the format will be the same unless there are substantial changes in the overall health situation and regulations.
  • Stuart J. Russell and Peter Norvig. "Artificial Intelligence A Modern Approach" (3. edition ). Pearson Education, 2010.
  • Zbigniew Michalewicz and David B. Fogel. "How to Solve It: Modern Heuristics", volume 2. Springer, 2004.
  • 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.
  • Michael Gelfond and Vladimir Lifschitz. "Classical negation in logic programs and disjunctive databases". New Generation Comput., 9(3–4):365–386, 1991.
  • A.E. Eiben and J.E. Smith. "Introduction to Evolutionary Computing", Springer, 2003.
  • Thomas Hammerl, Nysret Musliu and Werner Schafhauser. "Metaheuristic Algorithms and Tree Decomposition", Handbook of Computational Intelligence, pp 1255–1270, Springer, 2015.
  • Hans L. Bodlaender, Arie M.C.A. Koster. "Treewidth computations I. Upper bounds", Comput. 208(2): 259–275, 2010.
  • 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.
  • 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.

Veranstaltungskalender abonnieren (icalendar)

Vorlesung Introduction DS1, 6. November 2020 in Screencast Download 1 Download 2
Vorlesung Informed vs. Uninformed Search DS1, 13. November 2020 in Screencast Download 1 Download 2
Übung Tutorial 1 (Local Search) DS2, 13. November 2020 in Screencast Download
Vorlesung Local Search DS1, 20. November 2020 in Screencast Download 1 Download 2 Download 3
Vorlesung Tabu Search DS1, 27. November 2020 in Screencast Download 1 Download 2
Übung Tutorial 2 (Tabu Search) DS2, 27. November 2020 in Screencast Download
Vorlesung ASP 1 DS1, 4. Dezember 2020 in Screencast Download 1 Download 2 Download 3
Übung Tutorial 3 (ASP 1) DS2, 4. Dezember 2020 in Screencast Download
Vorlesung ASP 2 DS1, 11. Dezember 2020 in Screencast Download 1 Download 2 Download 3
Übung Tutorial 4 (ASP 2) DS2, 11. Dezember 2020 in Screencast Download
Vorlesung ASP 3 DS1, 18. Dezember 2020 in Screencast Download 1 Download 2 Download 3
Vorlesung CSP DS1, 8. Januar 2021 in Screencast
Übung Tutorial 5 (CSP) DS2, 8. Januar 2021 in Screencast Download
Vorlesung Evolutionary Algorithms DS1, 15. Januar 2021 in Screencast
Übung Tutorial 6 (EA 1) DS2, 15. Januar 2021 in Screencast Download
Vorlesung Structural Decompositions 1 DS1, 22. Januar 2021 in Screencast
Übung Tutorial 7 (Structural Decompositions) DS2, 22. Januar 2021 in Screencast
Vorlesung Structural Decompositions 2 DS1, 29. Januar 2021 in Screencast
Übung Tutorial 8 (Structural Decompositions 2) DS2, 29. Januar 2021 in Screencast
Vorlesung Q&A DS1, 5. Februar 2021 in APB E005


Kalender