International Center for Computational Logic - Benutzerbeiträge [de]

Advanced Problem Solving and Search (WS2025)

2026-05-11T11:43:26Z

Sarah Gaggl:

{{Vorlesung
|Title=Advanced Problem Solving and Search
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Tutors=Sarah Alice Gaggl; Hannes Straß
|Term=WS
|Year=2025
|Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI
|SWSLecture=2
|SWSExercise=2
|SWSPractical=0
|Exam type=nach Modulbeschreibung
|Description=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
*Evolutionary Algorithms, Genetic Algorithms
*Answer Set Programming
*Constraint Satisfaction Problems
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)

The course does not cover topics in the area of Machine Learning and Neural Networks.

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.

===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 tutorials, the students will analyze different problems and develop solutions for them.

===Prerequisites===
*Basic knowledge of theoretical computer science and Logic.
*Good English skills: teaching will be exclusively in English.

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

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.

'''Please, register for the course on the OPAL site''':

https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/51227885574

'''Registration to tutorial groups will be possible in OPAL after the first lecture on 14th October 2025'''.
===Exam===
Key information:
There are two forms of examination depending on your study program:

Students of the CMS Master, exchange students and students in the Computer Science Master:
*There will be a written exam. Dates and information will follow during the semester. There is no possibility to take the exam remotely.
*You must register in Selma or with your examination office.

Students with complex examinations:
*Please, schedule your oral exams with our secretary (cl@tu-dresden.de) after registering in Selma.

Inspection of written exam will be on Monday, 20th April, 14:00-15:00 in room APB 2040.
'''The 2nd date for inspecting the written exam will be on Monday, 18th May, 14:00-15:00 in room APB 2040.'''
|Literature=*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.
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Introduction
|Room=GÖR/0226/H
|Date=2025-10-14
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Informed vs. Uniformed Search
|Room=GÖR/0226/H
|Date=2025-10-21
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 1 (Traditional Search)
|Room=APB E007
|Date=2025-10-23
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 1 (Traditional Search)
|Room=APB E008
|Date=2025-10-27
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Local Search
|Room=GÖR/0226/H
|Date=2025-10-28
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 2 (Local Search)
|Room=APB E007
|Date=2025-10-30
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 2 (Local Search)
|Room=APB E008
|Date=2025-11-03
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Tabu Search
|Room=GÖR/0226/H
|Date=2025-11-04
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 3 (Tabu Search)
|Room=APB E007
|Date=2025-11-06
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 3 (Tabu Search)
|Room=APB E008
|Date=2025-11-24
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Evolutionary Algorithms
|Room=GÖR/0226/H
|Date=2025-11-25
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 4 (EA)
|Room=APB E007
|Date=2025-11-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 4 (EA)
|Room=APB E008
|Date=2025-12-01
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP I
|Room=GÖR/0226/H
|Date=2025-12-02
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 5 (ASP I)
|Room=APB E007
|Date=2025-12-04
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 5 (ASP I)
|Room=APB E008
|Date=2025-12-08
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP II
|Room=GÖR/0226/H
|Date=2025-12-09
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 6 (ASP II)
|Room=APB E007
|Date=2025-12-11
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 6 (ASP II)
|Room=APB E008
|Date=2025-12-15
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP III
|Room=GÖR/0226/H
|Date=2025-12-16
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 7 (ASP III)
|Room=APB E007
|Date=2025-12-18
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E008
|Date=2026-01-05
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=CSP
|Room=GÖR/0226/H
|Date=2026-01-06
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 8 (CSP)
|Room=APB E007
|Date=2026-01-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 8 (CSP)
|Room=APB E008
|Date=2026-01-12
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions I
|Room=GÖR/0226/H
|Date=2026-01-13
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 9 (TD I)
|Room=APB E007
|Date=2026-01-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 9 (TD I)
|Room=APB E008
|Date=2026-01-19
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions II
|Room=GÖR/0226/H
|Date=2026-01-20
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 10 (TD II)
|Room=APB E007
|Date=2026-01-22
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 10 (TD II)
|Room=APB E008
|Date=2026-01-26
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Q&A
|Room=GÖR/0226/H
|Date=2026-01-27
|DS=DS2
}}

Thema3516

2026-04-21T07:56:04Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Abschlussarbeit |Titel DE=Explaining Projected Answer Sets Using Faceted Reasoning |Titel EN=Explaining Projected Answer Sets Using Faceted Reasoning |Vorname=Paramita |Nachname=Choudhury |Abschlussarbeitstyp=Master |Betreuer=Sarah Gaggl |Forschungsgruppe=Logische Programmierung und Argumentation |Abschlussarbeitsstatus=Abgeschlossen |Abgabe=2025-11-27 |Beschreibung DE=Answer Set Programming (ASP) is a declarative paradigm for knowledge representation…“

{{Abschlussarbeit
|Titel DE=Explaining Projected Answer Sets Using Faceted Reasoning
|Titel EN=Explaining Projected Answer Sets Using Faceted Reasoning
|Vorname=Paramita
|Nachname=Choudhury
|Abschlussarbeitstyp=Master
|Betreuer=Sarah Gaggl
|Forschungsgruppe=Logische Programmierung und Argumentation
|Abschlussarbeitsstatus=Abgeschlossen
|Abgabe=2025-11-27
|Beschreibung DE=Answer Set Programming (ASP) is a declarative paradigm for knowledge representation
and reasoning, widely used for modeling combinatorial problems in artificial intelligence.
Modern ASP solvers can generate large numbers of answer sets, but exhaustive enumeration is often impractical due to computational constraints and the difficulty of interpreting
massive solution spaces. Projection addresses this challenge by reducing answer sets to
atoms of interest, but it introduces a new problem: users lack insight into what information was eliminated and whether the projected results adequately represent the underlying
diversity. This thesis presents a facet-based approach to explain projected answer sets in
ASP. We develop an algorithm that computes facet counts - measures of diversity based
on brave consequences - for projected-away solution spaces. By formulating integrity
constraints from projected answer sets and invoking facet-counting solvers, our approach
quantifies how much variation remains hidden behind each projection. We formalize this
through three key definitions and implement it as EPAS (Explaining Projected Answer
Sets), a tool supporting bounded-time execution and interactive navigation. Additionally, the system includes an interactive feature that enables users to explore structural
relationships within projected answer sets, transforming projection from a black-box reduction into a transparent analytical process.
|Beschreibung EN=Answer Set Programming (ASP) is a declarative paradigm for knowledge representation
and reasoning, widely used for modeling combinatorial problems in artificial intelligence.
Modern ASP solvers can generate large numbers of answer sets, but exhaustive enumeration is often impractical due to computational constraints and the difficulty of interpreting
massive solution spaces. Projection addresses this challenge by reducing answer sets to
atoms of interest, but it introduces a new problem: users lack insight into what information was eliminated and whether the projected results adequately represent the underlying
diversity. This thesis presents a facet-based approach to explain projected answer sets in
ASP. We develop an algorithm that computes facet counts - measures of diversity based
on brave consequences - for projected-away solution spaces. By formulating integrity
constraints from projected answer sets and invoking facet-counting solvers, our approach
quantifies how much variation remains hidden behind each projection. We formalize this
through three key definitions and implement it as EPAS (Explaining Projected Answer
Sets), a tool supporting bounded-time execution and interactive navigation. Additionally, the system includes an interactive feature that enables users to explore structural
relationships within projected answer sets, transforming projection from a black-box reduction into a transparent analytical process.
}}

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-20T06:13:14Z

Sarah Gaggl:

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026. '''Write a mail to Sarah Gaggl for registration to the seminar and topic selection!'''

# <s>Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6 </s>
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# <s>Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26</s>
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal:
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/53986033664/CourseNode/1775788782591287005
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
|Download=SeminarLBKR2026 L1.pdf
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=How to write a seminar paper
|Room=APB E005
|Date=2026-04-20
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=How to write a review and how to give a presentation
|Room=APB E005
|Date=2026-04-27
|DS=DS6
}}

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-16T10:41:36Z

Sarah Gaggl:

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026. '''Write a mail to Sarah Gaggl for registration to the seminar and topic selection!'''

# <s>Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6 </s>
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal:
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/53986033664/CourseNode/1775788782591287005
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
|Download=SeminarLBKR2026 L1.pdf
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=How to write a seminar paper
|Room=APB E005
|Date=2026-04-20
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=How to write a review and how to give a presentation
|Room=APB E005
|Date=2026-04-27
|DS=DS6
}}

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-16T10:39:49Z

Sarah Gaggl:

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026. '''Write a mail to Sarah Gaggl for registration to the seminar and topic selection!'''

# <s>Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6 </s>
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal:
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/53986033664/CourseNode/1775788782591287005
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
|Download=SeminarLBKR2026 L1.pdf
}}

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-16T10:28:48Z

Sarah Gaggl:

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026. '''Write a mail to Sarah Gaggl for registration of the seminar and topic selection!'''

# <s>Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6 </s>
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal:
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/53986033664/CourseNode/1775788782591287005
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
|Download=SeminarLBKR2026 L1.pdf
}}

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-16T10:28:20Z

Sarah Gaggl:

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026. '''Write a mail to Sarah Gaggl for registration of the seminar and topic selection!'''

<s># Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6 </s>
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal:
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/53986033664/CourseNode/1775788782591287005
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
|Download=SeminarLBKR2026 L1.pdf
}}

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-16T10:26:56Z

Sarah Gaggl:

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026. '''Write a mail to Sarah Gaggl for registration of the seminar and topic selection!'''

# Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal:
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/53986033664/CourseNode/1775788782591287005
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
|Download=SeminarLBKR2026 L1.pdf
}}

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-13T15:14:20Z

Sarah Gaggl:

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026.

# Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal:
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/53986033664/CourseNode/1775788782591287005
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
|Download=SeminarLBKR2026 L1.pdf
}}

Datei:SeminarLBKR2026 L1.pdf

2026-04-13T15:14:16Z

Sarah Gaggl:

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-10T06:49:02Z

Sarah Gaggl:

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026.

# Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal:
https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/53986033664/CourseNode/1775788782591287005
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
}}

Seminar Logic-Based Knowledge Representation (SS2026)

2026-04-02T12:18:58Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Vorlesung |Title=Seminar Logic-Based Knowledge Representation |Research group=Computational Logic; Logische Programmierung und Argumentation |Lecturers=Sarah Alice Gaggl |Term=SS |Year=2026 |Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS |SWSLecture=0 |SWSExercise=2 |SWSPractical=0 |Exam type=Hausarbeit, Referat, nach Modulbeschreibung |Description====Course Description=== This seminar intends to introduce to selected topics of…“

{{Vorlesung
|Title=Seminar Logic-Based Knowledge Representation
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Term=SS
|Year=2026
|Module=CMS-SEM-A, INF-04-HS, INF-AQUA, INF-D-940, INF-PM-FOR, MCL-PS
|SWSLecture=0
|SWSExercise=2
|SWSPractical=0
|Exam type=Hausarbeit, Referat, nach Modulbeschreibung
|Description====Course Description===

This seminar intends to introduce to selected topics of an active research area in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic '''Explanations for logic programs'''.

===Prerequisites===
Students are expected to be familiar with logic and in particular with logic programming.

===Seminar Plan===
The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 13th 2026.

# Contrastive Explanations for Answer-Set Programs https://link.springer.com/chapter/10.1007/978-3-031-43619-2_6
# Explaining Answer-Set Programs with Abstract Constraint Atoms https://www.ijcai.org/proceedings/2023/356
# Why This and Not That? A Logic-Based Framework for Contrastive Explanations https://link.springer.com/chapter/10.1007/978-3-032-04587-4_4
# Strong Inconsistency in Nonmonotonic Reasoning https://www.ijcai.org/proceedings/2017/125
# Answer Set Explanations via Preferred Unit-Provable Unsatisfiable Subsets https://link.springer.com/chapter/10.1007/978-3-031-74209-5_15
# Advancements in xASP, an XAI System for Answer Set Programming https://ceur-ws.org/Vol-3428/paper2.pdf
# Model Reconciliation in Logic Programs https://link.springer.com/chapter/10.1007/978-3-030-75775-5_26
# Witnesses for Answer Sets of Basic Logic Programs https://www.ijcai.org/proceedings/2025/523

===Examination===

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

===Organisation===
The course material is available in Opal: (follows soon)
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Seminar
|Title=Introduction - Topic selection
|Room=APB E005
|Date=2026-04-13
|DS=DS6
}}

Advanced Problem Solving and Search (WS2025)

2026-04-01T10:33:21Z

Sarah Gaggl:

{{Vorlesung
|Title=Advanced Problem Solving and Search
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Tutors=Sarah Alice Gaggl; Hannes Straß
|Term=WS
|Year=2025
|Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI
|SWSLecture=2
|SWSExercise=2
|SWSPractical=0
|Exam type=nach Modulbeschreibung
|Description=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
*Evolutionary Algorithms, Genetic Algorithms
*Answer Set Programming
*Constraint Satisfaction Problems
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)

The course does not cover topics in the area of Machine Learning and Neural Networks.

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.

===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 tutorials, the students will analyze different problems and develop solutions for them.

===Prerequisites===
*Basic knowledge of theoretical computer science and Logic.
*Good English skills: teaching will be exclusively in English.

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

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.

'''Please, register for the course on the OPAL site''':

https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/51227885574

'''Registration to tutorial groups will be possible in OPAL after the first lecture on 14th October 2025'''.
===Exam===
Key information:
There are two forms of examination depending on your study program:

Students of the CMS Master, exchange students and students in the Computer Science Master:
*There will be a written exam. Dates and information will follow during the semester. There is no possibility to take the exam remotely.
*You must register in Selma or with your examination office.

Students with complex examinations:
*Please, schedule your oral exams with our secretary (cl@tu-dresden.de) after registering in Selma.

'''Inspection of written exam will be on Monday, 20th April, 14:00-15:00 in room APB 2040."
|Literature=*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.
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Introduction
|Room=GÖR/0226/H
|Date=2025-10-14
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Informed vs. Uniformed Search
|Room=GÖR/0226/H
|Date=2025-10-21
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 1 (Traditional Search)
|Room=APB E007
|Date=2025-10-23
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 1 (Traditional Search)
|Room=APB E008
|Date=2025-10-27
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Local Search
|Room=GÖR/0226/H
|Date=2025-10-28
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 2 (Local Search)
|Room=APB E007
|Date=2025-10-30
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 2 (Local Search)
|Room=APB E008
|Date=2025-11-03
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Tabu Search
|Room=GÖR/0226/H
|Date=2025-11-04
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 3 (Tabu Search)
|Room=APB E007
|Date=2025-11-06
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 3 (Tabu Search)
|Room=APB E008
|Date=2025-11-24
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Evolutionary Algorithms
|Room=GÖR/0226/H
|Date=2025-11-25
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 4 (EA)
|Room=APB E007
|Date=2025-11-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 4 (EA)
|Room=APB E008
|Date=2025-12-01
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP I
|Room=GÖR/0226/H
|Date=2025-12-02
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 5 (ASP I)
|Room=APB E007
|Date=2025-12-04
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 5 (ASP I)
|Room=APB E008
|Date=2025-12-08
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP II
|Room=GÖR/0226/H
|Date=2025-12-09
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 6 (ASP II)
|Room=APB E007
|Date=2025-12-11
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 6 (ASP II)
|Room=APB E008
|Date=2025-12-15
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP III
|Room=GÖR/0226/H
|Date=2025-12-16
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 7 (ASP III)
|Room=APB E007
|Date=2025-12-18
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E008
|Date=2026-01-05
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=CSP
|Room=GÖR/0226/H
|Date=2026-01-06
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 8 (CSP)
|Room=APB E007
|Date=2026-01-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 8 (CSP)
|Room=APB E008
|Date=2026-01-12
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions I
|Room=GÖR/0226/H
|Date=2026-01-13
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 9 (TD I)
|Room=APB E007
|Date=2026-01-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 9 (TD I)
|Room=APB E008
|Date=2026-01-19
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions II
|Room=GÖR/0226/H
|Date=2026-01-20
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 10 (TD II)
|Room=APB E007
|Date=2026-01-22
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 10 (TD II)
|Room=APB E008
|Date=2026-01-26
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Q&A
|Room=GÖR/0226/H
|Date=2026-01-27
|DS=DS2
}}

Sarah Alice Gaggl

2026-01-21T12:08:23Z

Sarah Gaggl:

{{Mitarbeiter
|Vorname=Sarah Alice
|Nachname=Gaggl
|Akademischer Titel=Dr.
|Forschungsgruppe=Logische Programmierung und Argumentation
|Stellung=Gruppenleiterin
|Ehemaliger=0
|Telefon=+49 351 463 38679
|Fax=+49 351 463 32827
|Email=sarah.gaggl@tu-dresden.de
|Sekretariat Mail=cl@tu-dresden.de
|Matrix=@gaggl:tu-dresden.de
|Raum=APB 2017
|Bild=S-gaggl-3x2-klein.jpg
|Info=Seit Oktober 2020 bin ich Leiterin der Gruppe [[Logische_Programmierung_und_Argumentation | Logische Programmierung und Argumentation]] am Institut für Künstliche Intelligenz, TU-Dresden.
Von Oktober 2020 bis November 2024 war ich Projektleiterin des BMBF geförderten Projekts [[NAVAS | '''NAVAS - Navigation im Lösungsraum von Answer Sets''']].

Von 2019 bis 2022 war ich Principal Investigator im Sonderforschungsbereich 248 '''Grundlagen verständlicher Softwaresysteme''' ([[CPEC|Center for Perspicuous Computing, CPEC]]), der darauf abzielt die cyber-physikalische Welt für Menschen nachvollziehbar zu gestalten.
Von April 2013 bis September 2020 war ich Wissenschaftliche Mitarbeiterin in der [[Computational_Logic |Computational Logic Gruppe]] an der TU-Dresden.

In meiner Forschung konzentriere ich mich hauptsächlich auf die folgenden Themen:
*[[Abstrakte Argumentation/en |Abstract Argumentation ]]
*[[Answer Set Programming/en |Answer Set Programming (ASP)]]
*[[Wissensrepräsentation und logisches Schließen/en |Knowledge Representation]]

Bevor ich nach Dresden kam habe ich im März 2013 an der TU Wien promoviert. Von 2009 bis 2012 war ich Projektassistentin in der [http://www.dbai.tuwien.ac.at/ Database and Artificial Intelligence Gruppe] im [http://www.wwtf.at/index.php?lang=EN WWTF] Projekt [http://www.dbai.tuwien.ac.at/research/project/argumentation/ New Methods for Analyzing, Comparing, and Solving Argumentation Problems] unter der Leitung von [http://www.dbai.tuwien.ac.at/staff/woltran Stefan Woltran].

Weitere Informationen entnehme man meinem [[Media:cv_gaggl_work.pdf|CV]].
|Info EN=Since October 2020 I am the leader of the research group [[Logische_Programmierung_und_Argumentation | Logic Programming and Argumentation]] at the Institute of Artificial Intelligence, TU-Dresden.
From October 2020 till November 2024 I was the project leader of BMBF funded project [[NAVAS | '''NAVAS - Navigation Approaches for Answer Sets''']].
From 2019 till 2022 I was a principal investigator in the Transregional Collaborative Research Centre 248 [[CPEC |Center for Perspicuous Computing (CPEC)]] which aims at enabling comprehension in a cyber-physical world with the human in the loop.
From April 2013 till September 2020 I was a postdoctoral research assistant at the [[Computational_Logic |Computational Logic Group]] at the TU-Dresden.

My research interests are in (but not limmited to)
*[[Abstrakte Argumentation/en |Abstract Argumentation ]]
*[[Answer Set Programming/en |Answer Set Programming (ASP)]]
*[[Wissensrepräsentation und logisches Schließen/en |Knowledge Representation]]

Before joining the TU Dresden I received my PhD in Computer Science in 2013 at the Vienna University of Technology. From 2009 to 2012 I was working as a project research assistant in the [http://www.dbai.tuwien.ac.at/ Database and Artificial Intelligence Group] at the [http://www.wwtf.at/index.php?lang=EN WWTF] project [http://www.dbai.tuwien.ac.at/research/project/argumentation/ New Methods for Analyzing, Comparing, and Solving Argumentation Problems] under the supervision of [http://www.dbai.tuwien.ac.at/staff/woltran Stefan Woltran].

For further information have a look at my [[Media:cv_gaggl_work.pdf|CV]].
|DBLP=https://dblp.org/pid/75/5285.html
|Google Scholar=http://scholar.google.de/citations?user=i2uRICsAAAAJ&hl=de&oi=ao
|Publikationen anzeigen=1
|Abschlussarbeiten anzeigen=1
|Projekte anzeigen=0
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Abstrakte Argumentation
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Answer Set Programming
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Wissensrepräsentation und logisches Schließen
}}
{{#subobject:
|Vorname=Sarah Alice
|Nachname=Gaggl
|Akademischer Titel=Dr.
|Forschungsgruppe=Computational Logic
|Stellung=Wissenschaftliche Mitarbeiterin
|Ehemaliger=1
|Telefon=+49 351 463 38679
|Fax=+49 351 463 32827
|Email=sarah.gaggl@tu-dresden.de
|Raum=APB 2034
|Bild=TUD 8253 hi res 2.jpg
|Info=<br>
|Info EN=<br>
|Publikationen anzeigen=1
|Abschlussarbeiten anzeigen=1
|@category=Mitarbeiter
}}

Datei:Cv gaggl work.pdf

2026-01-20T15:11:05Z

Sarah Gaggl: Sarah Gaggl lud eine neue Version von Datei:Cv gaggl work.pdf hoch

Datei:Cv gaggl work.pdf

2026-01-20T15:05:48Z

Sarah Gaggl: Sarah Gaggl lud eine neue Version von Datei:Cv gaggl work.pdf hoch

Inproceedings3091

2026-01-16T13:19:48Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Sarah Alice
|ErsterAutorNachname=Gaggl
|FurtherAuthors=Sebastian Rudolph; Lukas Schweizer
}}
{{Inproceedings
|Referiert=1
|Title=Fixed-Domain Reasoning for Description Logics
|To appear=0
|Year=2016
|Month=September
|Booktitle=Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI 2016)
|Pages=819 - 827
|Publisher=IOS Press
|Editor=Gal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hüllermeier, Virginia Dignum, Frank Dignum, Frank van Harmelen
|Series=Frontiers in Artificial Intelligence and Applications
|Volume=285
}}
{{Publikation Tool
|Tool=Wolpertinger
}}
{{Publikation Details
|Abstract=After decades of fruitful research, description logics (DLs) have evolved into a de facto standard in logic-based knowledge representation. In particular, they serve as the formal basis of the standardized and very popular web ontology language (OWL), which also comes with the advantage of readily available user-friendly modeling tools and optimized reasoning engines. In the course of the wide-spread adoption
of OWL and DLs, situations have been observed where logically less skilled practitioners are (ab)using these formalisms as constraint languages adopting a closed-world assumption, contrary to the open-world semantics imposed by the classical definitions and the standards.
To provide a clear theoretical basis and inferencing support for this often practically reasonable “off-label use” we propose an alternative formal semantics reflecting the intuitive understanding of such scenarios. To that end, we introduce the fixed-domain semantics and argue that this semantics gives rise to an interesting new inferencing task: model enumeration.
We describe how the new semantics can be axiomatized in very expressive DLs. We thoroughly investigate the complexities
for standard reasoning as well as query answering under the fixed-domain semantics for a wide range of DLs. Further, we present an implementation of a fixed-domain DL reasoner based on a translation into answer set programming (ASP) which is competitive with alternative approaches for standard reasoning tasks and provides the added functionality
of model enumeration.
|ISBN=978-1-61499-672-9
|Download=GagglRS2016a.pdf
|DOI Name=10.3233/978-1-61499-672-9-819
|Projekt=QuantLA
|Forschungsgruppe=Computational Logic, Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Beschreibungslogiken
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Answer Set Programming
}}

Inproceedings3432

2025-12-16T12:54:15Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Michelle
|ErsterAutorNachname=Kornherr
|FurtherAuthors=Augusto B. Correa; Sarah Alice Gaggl; Markus Hecher; Dominik Rusovac; David Speck; Johannes K. Fichte; Daniel Gnad
}}
{{Inproceedings
|Referiert=1
|Title=Graphical Navigation in Solution Spaces using PlanPilot
|To appear=0
|Year=2025
|Month=November
|Booktitle=System Demonstrations and Exhibits program at ICAPS 2025 (The 35th International Conference on Automated Planning and Scheduling)
}}
{{Publikation Details
|Bild=ICAPS25-Demo paper 3-2.pdf
|Abstract=Many planning applications require not only a single solution but benefit substantially from having a set of possible plans from which users can select according to preferences. Surprisingly, planning research has primarily focused on quickly finding single plans for decades. Only recently have researchers started to investigate plan enumeration by top-k planning, offering more flexibility to the user. But simply enumerating the k best plans is far from targeted due to the time-consuming nature of enumeration, likely feeding many similar plans to the user, and forcing the user to define filters beforehand. In fact, in extensive search spaces, enumeration is hardly practical. We present an approach and a tool called PlanPilot to navigate solution spaces of planning tasks iteratively and interactively. We build on answer-set programming (ASP) to restrict the plan space. To that end, we employ facets, which are meaningful actions that appear in some, but not all plans. Enforcing or forbidding such facets allows for navigating even large plan spaces while ensuring desired properties quickly and step by step.
|Download=ICAPS25-Demo paper 3-2.pdf
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl}}

Inproceedings3432

2025-12-15T15:07:29Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Michelle
|ErsterAutorNachname=Kornherr
|FurtherAuthors=Augusto B. Correa; Sarah Alice Gaggl; Markus Hecher; Dominik Rusovac; David Speck; Johannes K. Fichte; Daniel Gnad
}}
{{Inproceedings
|Referiert=1
|Title=Graphical Navigation in Solution Spaces using PlanPilot
|To appear=1
|Year=2025
|Booktitle=System Demonstrations and Exhibits program at ICAPS 2025 (The 35th International Conference on Automated Planning and Scheduling)
}}
{{Publikation Details
|Bild=ICAPS25-Demo paper 3-2.pdf
|Abstract=Many planning applications require not only a single solution but benefit substantially from having a set of possible plans from which users can select according to preferences. Surprisingly, planning research has primarily focused on quickly finding single plans for decades. Only recently have researchers started to investigate plan enumeration by top-k planning, offering more flexibility to the user. But simply enumerating the k best plans is far from targeted due to the time-consuming nature of enumeration, likely feeding many similar plans to the user, and forcing the user to define filters beforehand. In fact, in extensive search spaces, enumeration is hardly practical. We present an approach and a tool called PlanPilot to navigate solution spaces of planning tasks iteratively and interactively. We build on answer-set programming (ASP) to restrict the plan space. To that end, we employ facets, which are meaningful actions that appear in some, but not all plans. Enforcing or forbidding such facets allows for navigating even large plan spaces while ensuring desired properties quickly and step by step.
|Download=ICAPS25-Demo paper 3-2.pdf
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl}}

Inproceedings3432

2025-12-15T15:06:26Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Michelle
|ErsterAutorNachname=Kornherr
|FurtherAuthors=Augusto B. Correa; Sarah Alice Gaggl; Markus Hecher; Dominik Rusovac; David Speck; Johannes K. Fichte; Daniel Gnad
}}
{{Inproceedings
|Referiert=1
|Title=Graphical Navigation in Solution Spaces using PlanPilot
|To appear=1
|Year=2025
|Booktitle=System Demonstrations and Exhibits program at ICAPS 2025 (The 35th International Conference on Automated Planning and Scheduling)
}}
{{Publikation Details
|Bild=ICAPS25-Demo paper 3-2.pdf
|Abstract=Many planning applications require not only a single solution but benefit substantially from having a set of possible plans from which users can select according to preferences. Surprisingly, planning research has primarily focused on quickly finding single plans for decades. Only recently have researchers started to investigate plan enumeration by top-k planning, offering more flexibility to the user. But simply enumerating the k best plans is far from targeted due to the time-consuming nature of enumeration, likely feeding many similar plans to the user, and forcing the user to define filters beforehand. In fact, in extensive search spaces, enumeration is hardly practical. We present an approach and a tool called PlanPilot to navigate solution spaces of planning tasks iteratively and interactively. We build on answer-set programming (ASP) to restrict the plan space. To that end, we employ facets, which are meaningful actions that appear in some, but not all plans. Enforcing or forbidding such facets allows for navigating even large plan spaces while ensuring desired properties quickly and step by step.
|Download=ICAPS25-Demo paper 3-2.pdf
|Link=https://www.youtube.com/watch?v=75UngGNr5bc
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl}}

Inproceedings3419

2025-11-17T09:24:00Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Martin
|ErsterAutorNachname=Diller
|FurtherAuthors=Sarah Alice Gaggl; Philipp Hanisch; Giuseppina Monterosso; Fritz Rauschenbach
}}
{{Inproceedings
|Referiert=1
|Title=Grounding Rule-Based Argumentation Using Datalog
|To appear=0
|Year=2025
|Month=November
|Booktitle=Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning (KR 2025)
|Pages=281–292
|Publisher=IJCAI Organization
|Editor=Magdalena Ortiz, Renata Wassermann, Torsten Schaub
}}
{{Publikation Details
|Abstract=ASPIC+ is one of the main general frameworks for rule-based argumentation for AI. Although first-order rules are commonly used in ASPIC+ examples, most existing approaches to reason over rule-based argumentation only support propositional rules. To enable reasoning over first-order instances, a preliminary grounding step is required. As groundings can lead to an exponential increase in the size of the input theories, intelligent procedures are needed. However, there is a lack of dedicated solutions for ASPIC+. Therefore, we propose an intelligent grounding procedure that keeps the size of the grounding manageable while preserving the correctness of the reasoning process. To this end, we translate the first-order ASPIC+ instance into a Datalog program and query a Datalog engine to obtain ground substitutions to perform the grounding of rules and contraries. Additionally, we propose simplifications specific to the ASPIC+ formalism to avoid grounding of rules that have no influence on the reasoning process. Finally, we performed an empirical evaluation of a prototypical implementation to show scalability.
|ISBN=978-1-956792-08-9
|ISSN=2334-1033
|Download=Kr2025-0028-diller-et-al.pdf
|DOI Name=https://doi.org/10.24963/kr.2025/28
|Projekt=SECAI, SEMECO-Q2
|Forschungsgruppe=Logische Programmierung und Argumentation, Wissensbasierte Systeme
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Abstrakte Argumentation
}}

Inproceedings3419

2025-11-17T09:22:44Z

Sarah Gaggl:

Datei:Kr2025-0028-diller-et-al.pdf

2025-11-17T09:22:39Z

Sarah Gaggl:

Inproceedings3419

2025-11-17T09:18:30Z

Sarah Gaggl:

Inproceedings3420

2025-11-17T09:15:51Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Daniel
|ErsterAutorNachname=Gnad
|FurtherAuthors=Markus Hecher; Sarah Alice Gaggl; Dominik Rusovac; David Jakob Speck; Johannes K. Fichte
}}
{{Inproceedings
|Referiert=1
|Title=Interactive Exploration of Plan Spaces
|To appear=0
|Year=2025
|Month=November
|Booktitle=Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning — KR in the Wild (KR 2025)
|Pages=599–609
|Publisher=IJCAI Organization
|Editor=Magdalena Ortiz, Renata Wassermann, Torsten Schaub
}}
{{Publikation Details
|Abstract=Many planning applications require not only a single solution but
benefit substantially from having a set of possible plans from which
users can select, for example, when explaining plans. For
decades, research in classical AI planning has primarily focused on
quickly finding single plans.
Only recently researchers have started to investigate preferences,
enumerate plans by top-k planning, or count plans to reason about
the plan space.
Unfortunately, reasoning about the plan space is computationally
extremely hard and feeding many similar plans to the user is hardly
practical.
To circumvent computational shortcomings while still being able to
reason about variability in plans, faceted actions have been
introduced very recently.
These are meaningful actions that can be used by some plan but are
not required by all plans. Enforcing or forbidding such facets
allows for navigating even large plan spaces while ensuring desired
properties quickly and step by step.
In this paper, we illustrate an industrial challenge, the Beluga
logistics problem of Airbus, where reasoning with facets enables
targeted plan space navigation. We present an approach to handle
large plan spaces iteratively and present a tool that we call planpilot.
|ISBN=978-1-956792-08-9
|ISSN=2334-1033
|Download=GHGRSF2025-preprint.pdf
|Slides=KR2025-Interactive-Plan-spaces-Gaggl.pdf
|DOI Name=https://doi.org/10.24963/kr.2025/58
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Answer Set Programming
}}

Datei:KR2025-Interactive-Plan-spaces-Gaggl.pdf

2025-11-17T09:11:46Z

Sarah Gaggl:

Inproceedings3432

2025-10-13T07:01:14Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Michelle
|ErsterAutorNachname=Kornherr
|FurtherAuthors=Augusto B. Correa; Sarah Alice Gaggl; Markus Hecher; Dominik Rusovac; David Speck; Johannes K. Fichte; Daniel Gnad
}}
{{Inproceedings
|Referiert=1
|Title=Graphical Navigation in Solution Spaces using PlanPilot
|To appear=1
|Year=2025
|Booktitle=System Demonstrations and Exhibits program at ICAPS 2025 (The 35th International Conference on Automated Planning and Scheduling)
}}
{{Publikation Details
|Bild=ICAPS25-Demo paper 3-2.pdf
|Abstract=Many planning applications require not only a single solution but benefit substantially from having a set of possible plans from which users can select according to preferences. Surprisingly, planning research has primarily focused on quickly finding single plans for decades. Only recently have researchers started to investigate plan enumeration by top-k planning, offering more flexibility to the user. But simply enumerating the k best plans is far from targeted due to the time-consuming nature of enumeration, likely feeding many similar plans to the user, and forcing the user to define filters beforehand. In fact, in extensive search spaces, enumeration is hardly practical. We present an approach and a tool called PlanPilot to navigate solution spaces of planning tasks iteratively and interactively. We build on answer-set programming (ASP) to restrict the plan space. To that end, we employ facets, which are meaningful actions that appear in some, but not all plans. Enforcing or forbidding such facets allows for navigating even large plan spaces while ensuring desired properties quickly and step by step.
|Download=ICAPS25-Demo paper 3-2.pdf
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl}}

Inproceedings3432

2025-10-13T07:00:08Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Michelle
|ErsterAutorNachname=Kornherr
|FurtherAuthors=Augusto B. Correa; Sarah Alice Gaggl; Markus Hecher; Dominik Rusovac; David Speck; Johannes K. Fichte; Daniel Gnad
}}
{{Inproceedings
|Referiert=1
|Title=Graphical Navigation in Solution Spaces using PlanPilot
|To appear=1
|Year=2025
|Booktitle=System Demonstrations and Exhibits program at ICAPS 2025 (The 35th International Conference on Automated Planning and Scheduling)
}}
{{Publikation Details
|Bild=ICAPS25-Demo paper 3-2.pdf
|Abstract=Many planning applications require not only a single solution but benefit substantially from having a set of possible plans from which users can select according to preferences. Surprisingly, planning research has primarily focused on quickly finding single plans for decades. Only recently have researchers started to investigate plan enumeration by top-k planning, offering more flexibility to the user. But simply enumerating the k best plans is far from targeted due to the time-consuming nature of enumeration, likely feeding many similar plans to the user, and forcing the user to define filters beforehand. In fact, in extensive search spaces, enumeration is hardly practical. We present an approach and a tool called PlanPilot to navigate solution spaces of planning tasks iteratively and interactively. We build on answer-set programming (ASP) to restrict the plan space. To that end, we employ facets, which are meaningful actions that appear in some, but not all plans. Enforcing or forbidding such facets allows for navigating even large plan spaces while ensuring desired properties quickly and step by step.
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl}}

Datei:ICAPS25-Demo paper 3-2.pdf

2025-10-13T07:00:03Z

Sarah Gaggl:

Advanced Problem Solving and Search (WS2025)

2025-09-23T08:25:31Z

Sarah Gaggl:

{{Vorlesung
|Title=Advanced Problem Solving and Search
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Tutors=Sarah Alice Gaggl; Hannes Straß
|Term=WS
|Year=2025
|Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI
|SWSLecture=2
|SWSExercise=2
|SWSPractical=0
|Exam type=nach Modulbeschreibung
|Description=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
*Evolutionary Algorithms, Genetic Algorithms
*Answer Set Programming
*Constraint Satisfaction Problems
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)

The course does not cover topics in the area of Machine Learning and Neural Networks.

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.

===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 tutorials, the students will analyze different problems and develop solutions for them.

===Prerequisites===
*Basic knowledge of theoretical computer science and Logic.
*Good English skills: teaching will be exclusively in English.

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

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.

'''Please, register for the course on the OPAL site''':

https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/51227885574

'''Registration to tutorial groups will be possible in OPAL after the first lecture on 14th October 2025'''.
===Exam===
Key information:
There are two forms of examination depending on your study program:

Students of the CMS Master, exchange students and students in the Computer Science Master:
*There will be a written exam. Dates and information will follow during the semester. There is no possibility to take the exam remotely.
*You must register in Selma or with your examination office.

Students with complex examinations:
*Please, schedule your oral exams with our secretary (cl@tu-dresden.de) after registering in Selma.
|Literature=*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.
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Introduction
|Room=GÖR/0226/H
|Date=2025-10-14
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Informed vs. Uniformed Search
|Room=GÖR/0226/H
|Date=2025-10-21
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 1 (Traditional Search)
|Room=APB E007
|Date=2025-10-23
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 1 (Traditional Search)
|Room=APB E008
|Date=2025-10-27
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Local Search
|Room=GÖR/0226/H
|Date=2025-10-28
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 2 (Local Search)
|Room=APB E007
|Date=2025-10-30
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 2 (Local Search)
|Room=APB E008
|Date=2025-11-03
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Tabu Search
|Room=GÖR/0226/H
|Date=2025-11-04
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 3 (Tabu Search)
|Room=APB E007
|Date=2025-11-06
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 3 (Tabu Search)
|Room=APB E008
|Date=2025-11-24
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Evolutionary Algorithms
|Room=GÖR/0226/H
|Date=2025-11-25
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 4 (EA)
|Room=APB E007
|Date=2025-11-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 4 (EA)
|Room=APB E008
|Date=2025-12-01
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP I
|Room=GÖR/0226/H
|Date=2025-12-02
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 5 (ASP I)
|Room=APB E007
|Date=2025-12-04
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 5 (ASP I)
|Room=APB E008
|Date=2025-12-08
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP II
|Room=GÖR/0226/H
|Date=2025-12-09
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 6 (ASP II)
|Room=APB E007
|Date=2025-12-11
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 6 (ASP II)
|Room=APB E008
|Date=2025-12-15
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP III
|Room=GÖR/0226/H
|Date=2025-12-16
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 7 (ASP III)
|Room=APB E007
|Date=2025-12-18
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E008
|Date=2026-01-05
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=CSP
|Room=GÖR/0226/H
|Date=2026-01-06
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 8 (CSP)
|Room=APB E007
|Date=2026-01-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 8 (CSP)
|Room=APB E008
|Date=2026-01-12
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions I
|Room=GÖR/0226/H
|Date=2026-01-13
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 9 (TD I)
|Room=APB E007
|Date=2026-01-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 9 (TD I)
|Room=APB E008
|Date=2026-01-19
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions II
|Room=GÖR/0226/H
|Date=2026-01-20
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 10 (TD II)
|Room=APB E007
|Date=2026-01-22
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 10 (TD II)
|Room=APB E008
|Date=2026-01-26
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Q&A
|Room=GÖR/0226/H
|Date=2026-01-27
|DS=DS2
}}

Advanced Problem Solving and Search (WS2025)

2025-09-23T08:24:45Z

Sarah Gaggl:

{{Vorlesung
|Title=Advanced Problem Solving and Search
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Tutors=Sarah Alice Gaggl; Hannes Straß
|Term=WS
|Year=2025
|Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI
|SWSLecture=2
|SWSExercise=2
|SWSPractical=0
|Exam type=nach Modulbeschreibung
|Description=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
*Evolutionary Algorithms, Genetic Algorithms
*Answer Set Programming
*Constraint Satisfaction Problems
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)

The course does not cover topics in the area of Machine Learning and Neural Networks.

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.

===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 tutorials, the students will analyze different problems and develop solutions for them.

===Prerequisites===
*Basic knowledge of theoretical computer science and Logic.
*Good English skills: teaching will be exclusively in English.

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

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.

Please, register for the course on the OPAL site:

https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/51227885574

Registration to tutorial groups will be possible in OPAL after the first lecture on 14th October 2025.
===Exam===
Key information:
There are two forms of examination depending on your study program:

Students of the CMS Master, exchange students and students in the Computer Science Master:
*There will be a written exam. Dates and information will follow during the semester. There is no possibility to take the exam remotely.
*You must register in Selma or with your examination office.

Students with complex examinations:
*Please, schedule your oral exams with our secretary (cl@tu-dresden.de) after registering in Selma.
|Literature=*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.
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Introduction
|Room=GÖR/0226/H
|Date=2025-10-14
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Informed vs. Uniformed Search
|Room=GÖR/0226/H
|Date=2025-10-21
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 1 (Traditional Search)
|Room=APB E007
|Date=2025-10-23
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 1 (Traditional Search)
|Room=APB E008
|Date=2025-10-27
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Local Search
|Room=GÖR/0226/H
|Date=2025-10-28
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 2 (Local Search)
|Room=APB E007
|Date=2025-10-30
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 2 (Local Search)
|Room=APB E008
|Date=2025-11-03
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Tabu Search
|Room=GÖR/0226/H
|Date=2025-11-04
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 3 (Tabu Search)
|Room=APB E007
|Date=2025-11-06
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 3 (Tabu Search)
|Room=APB E008
|Date=2025-11-24
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Evolutionary Algorithms
|Room=GÖR/0226/H
|Date=2025-11-25
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 4 (EA)
|Room=APB E007
|Date=2025-11-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 4 (EA)
|Room=APB E008
|Date=2025-12-01
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP I
|Room=GÖR/0226/H
|Date=2025-12-02
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 5 (ASP I)
|Room=APB E007
|Date=2025-12-04
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 5 (ASP I)
|Room=APB E008
|Date=2025-12-08
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP II
|Room=GÖR/0226/H
|Date=2025-12-09
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 6 (ASP II)
|Room=APB E007
|Date=2025-12-11
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 6 (ASP II)
|Room=APB E008
|Date=2025-12-15
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP III
|Room=GÖR/0226/H
|Date=2025-12-16
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 7 (ASP III)
|Room=APB E007
|Date=2025-12-18
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E008
|Date=2026-01-05
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=CSP
|Room=GÖR/0226/H
|Date=2026-01-06
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 8 (CSP)
|Room=APB E007
|Date=2026-01-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 8 (CSP)
|Room=APB E008
|Date=2026-01-12
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions I
|Room=GÖR/0226/H
|Date=2026-01-13
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 9 (TD I)
|Room=APB E007
|Date=2026-01-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 9 (TD I)
|Room=APB E008
|Date=2026-01-19
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions II
|Room=GÖR/0226/H
|Date=2026-01-20
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 10 (TD II)
|Room=APB E007
|Date=2026-01-22
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 10 (TD II)
|Room=APB E008
|Date=2026-01-26
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Q&A
|Room=GÖR/0226/H
|Date=2026-01-27
|DS=DS2
}}

Advanced Problem Solving and Search (WS2025)

2025-09-23T08:16:42Z

Sarah Gaggl:

{{Vorlesung
|Title=Advanced Problem Solving and Search
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Tutors=Sarah Alice Gaggl; Hannes Straß
|Term=WS
|Year=2025
|Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI
|SWSLecture=2
|SWSExercise=2
|SWSPractical=0
|Exam type=nach Modulbeschreibung
|Description=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
*Evolutionary Algorithms, Genetic Algorithms
*Answer Set Programming
*Constraint Satisfaction Problems
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)

The course does not cover topics in the area of Machine Learning and Neural Networks.

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.

===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 tutorials, the students will analyze different problems and develop solutions for them.

===Prerequisites===
*Basic knowledge of theoretical computer science and Logic.
*Good English skills: teaching will be exclusively in English.

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

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.

Please, register for the course on the OPAL site:

https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/51227885574

===Exam===
Key information:
There are two forms of examination depending on your study program:

Students of the CMS Master, exchange students and students in the Computer Science Master:
*There will be a written exam. Dates and information will follow during the semester. There is no possibility to take the exam remotely.
*You must register in Selma or with your examination office.

Students with complex examinations:
*Please, schedule your oral exams with our secretary (cl@tu-dresden.de) after registering in Selma.
|Literature=*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.
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Introduction
|Room=GÖR/0226/H
|Date=2025-10-14
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Informed vs. Uniformed Search
|Room=GÖR/0226/H
|Date=2025-10-21
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 1 (Traditional Search)
|Room=APB E007
|Date=2025-10-23
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 1 (Traditional Search)
|Room=APB E008
|Date=2025-10-27
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Local Search
|Room=GÖR/0226/H
|Date=2025-10-28
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 2 (Local Search)
|Room=APB E007
|Date=2025-10-30
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 2 (Local Search)
|Room=APB E008
|Date=2025-11-03
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Tabu Search
|Room=GÖR/0226/H
|Date=2025-11-04
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 3 (Tabu Search)
|Room=APB E007
|Date=2025-11-06
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 3 (Tabu Search)
|Room=APB E008
|Date=2025-11-24
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Evolutionary Algorithms
|Room=GÖR/0226/H
|Date=2025-11-25
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 4 (EA)
|Room=APB E007
|Date=2025-11-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 4 (EA)
|Room=APB E008
|Date=2025-12-01
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP I
|Room=GÖR/0226/H
|Date=2025-12-02
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 5 (ASP I)
|Room=APB E007
|Date=2025-12-04
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 5 (ASP I)
|Room=APB E008
|Date=2025-12-08
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP II
|Room=GÖR/0226/H
|Date=2025-12-09
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 6 (ASP II)
|Room=APB E007
|Date=2025-12-11
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 6 (ASP II)
|Room=APB E008
|Date=2025-12-15
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP III
|Room=GÖR/0226/H
|Date=2025-12-16
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 7 (ASP III)
|Room=APB E007
|Date=2025-12-18
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E008
|Date=2026-01-05
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=CSP
|Room=GÖR/0226/H
|Date=2026-01-06
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 8 (CSP)
|Room=APB E007
|Date=2026-01-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 8 (CSP)
|Room=APB E008
|Date=2026-01-12
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions I
|Room=GÖR/0226/H
|Date=2026-01-13
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 9 (TD I)
|Room=APB E007
|Date=2026-01-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 9 (TD I)
|Room=APB E008
|Date=2026-01-19
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions II
|Room=GÖR/0226/H
|Date=2026-01-20
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 10 (TD II)
|Room=APB E007
|Date=2026-01-22
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 10 (TD II)
|Room=APB E008
|Date=2026-01-26
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Q&A
|Room=GÖR/0226/H
|Date=2026-01-27
|DS=DS2
}}

Advanced Problem Solving and Search (WS2025)

2025-09-22T07:40:22Z

Sarah Gaggl:

{{Vorlesung
|Title=Advanced Problem Solving and Search
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Tutors=Sarah Alice Gaggl; Hannes Straß
|Term=WS
|Year=2025
|Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI
|SWSLecture=2
|SWSExercise=2
|SWSPractical=0
|Exam type=nach Modulbeschreibung
|Description=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
*Evolutionary Algorithms, Genetic Algorithms
*Answer Set Programming
*Constraint Satisfaction Problems
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)

The course does not cover topics in the area of Machine Learning and Neural Networks.

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.

===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 tutorials, the students will analyze different problems and develop solutions for them.

===Prerequisites===
*Basic knowledge of theoretical computer science and Logic.
*Good English skills: teaching will be exclusively in English.

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

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.

Please, register for the course on the OPAL site:

follows soon

===Exam===
Key information:
There are two forms of examination depending on your study program:

Students of the CMS Master, exchange students and students in the Computer Science Master:
*There will be a written exam. Dates and information will follow during the semester. There is no possibility to take the exam remotely.
*You must register in Selma or with your examination office.

Students with complex examinations:
*Please, schedule your oral exams with our secretary (cl@tu-dresden.de) after registering in Selma.
|Literature=*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.
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Introduction
|Room=GÖR/0226/H
|Date=2025-10-14
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Informed vs. Uniformed Search
|Room=GÖR/0226/H
|Date=2025-10-21
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 1 (Traditional Search)
|Room=APB E007
|Date=2025-10-23
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 1 (Traditional Search)
|Room=APB E008
|Date=2025-10-27
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Local Search
|Room=GÖR/0226/H
|Date=2025-10-28
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 2 (Local Search)
|Room=APB E007
|Date=2025-10-30
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 2 (Local Search)
|Room=APB E008
|Date=2025-11-03
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Tabu Search
|Room=GÖR/0226/H
|Date=2025-11-04
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 3 (Tabu Search)
|Room=APB E007
|Date=2025-11-06
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 3 (Tabu Search)
|Room=APB E008
|Date=2025-11-24
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Evolutionary Algorithms
|Room=GÖR/0226/H
|Date=2025-11-25
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 4 (EA)
|Room=APB E007
|Date=2025-11-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 4 (EA)
|Room=APB E008
|Date=2025-12-01
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP I
|Room=GÖR/0226/H
|Date=2025-12-02
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 5 (ASP I)
|Room=APB E007
|Date=2025-12-04
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 5 (ASP I)
|Room=APB E008
|Date=2025-12-08
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP II
|Room=GÖR/0226/H
|Date=2025-12-09
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 6 (ASP II)
|Room=APB E007
|Date=2025-12-11
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 6 (ASP II)
|Room=APB E008
|Date=2025-12-15
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP III
|Room=GÖR/0226/H
|Date=2025-12-16
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 7 (ASP III)
|Room=APB E007
|Date=2025-12-18
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E008
|Date=2026-01-05
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=CSP
|Room=GÖR/0226/H
|Date=2026-01-06
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 8 (CSP)
|Room=APB E007
|Date=2026-01-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 8 (CSP)
|Room=APB E008
|Date=2026-01-12
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions I
|Room=GÖR/0226/H
|Date=2026-01-13
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 9 (TD I)
|Room=APB E007
|Date=2026-01-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 9 (TD I)
|Room=APB E008
|Date=2026-01-19
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions II
|Room=GÖR/0226/H
|Date=2026-01-20
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 10 (TD II)
|Room=APB E007
|Date=2026-01-22
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 10 (TD II)
|Room=APB E008
|Date=2026-01-26
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Q&A
|Room=GÖR/0226/H
|Date=2026-01-27
|DS=DS2
}}

Advanced Problem Solving and Search (WS2025)

2025-09-22T07:37:44Z

Sarah Gaggl:

{{Vorlesung
|Title=Advanced Problem Solving and Search
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Tutors=Sarah Alice Gaggl; Hannes Straß
|Term=WS
|Year=2025
|Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI
|SWSLecture=2
|SWSExercise=2
|SWSPractical=0
|Exam type=nach Modulbeschreibung
|Description=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
*Evolutionary Algorithms, Genetic Algorithms
*Answer Set Programming
*Constraint Satisfaction Problems
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)

The course does not cover topics in the area of Machine Learning and Neural Networks.

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.

===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 tutorials, the students will analyze different problems and develop solutions for them.

===Prerequisites===
*Basic knowledge of theoretical computer science and Logic.
*Good English skills: teaching will be exclusively in English.

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

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.

Please, register for the course on the OPAL site:

follows soon

===Exam===
Key information:
There are two forms of examination depending on your study program:

Students of the CMS Master, exchange students and students in the Computer Science Master:
*There will be a written exam. Dates and information will follow during the semester. There is no possibility to take the exam remotely.
*You must register in Selma or with your examination office.

Students with complex examinations:
*Please, schedule your oral exams with our secretary (cl@tu-dresden.de) after registering in Selma.
|Literature=*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.
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Introduction
|Room=GÖR/0226/H
|Date=2025-10-14
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Informed vs. Uniformed Search
|Room=GÖR/0226/H
|Date=2025-10-21
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 1 (Traditional Search)
|Room=APB E007
|Date=2025-10-23
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 1 (Traditional Search)
|Room=APB E008
|Date=2025-10-27
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Local Search
|Room=GÖR/0226/H
|Date=2025-10-28
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 2 (Local Search)
|Room=APB E007
|Date=2025-10-30
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 2 (Local Search)
|Room=APB E008
|Date=2025-11-03
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Tabu Search
|Room=GÖR/0226/H
|Date=2025-11-04
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 3 (Tabu Search)
|Room=APB E007
|Date=2025-11-06
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 3 (Tabu Search)
|Room=APB E008
|Date=2025-11-24
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Evolutionary Algorithms
|Room=GÖR/0226/H
|Date=2025-11-25
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 4 (EA)
|Room=APB E007
|Date=2025-11-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 4 (EA)
|Room=APB E008
|Date=2025-12-01
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP I
|Room=GÖR/0226/H
|Date=2025-12-02
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 5 (ASP I)
|Room=APB E007
|Date=2025-12-04
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 5 (ASP I)
|Room=APB E008
|Date=2025-12-08
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP II
|Room=GÖR/0226/H
|Date=2025-12-09
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 6 (ASP II)
|Room=APB E007
|Date=2025-12-11
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 6 (ASP II)
|Room=APB E008
|Date=2025-12-15
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP III
|Room=GÖR/0226/H
|Date=2025-12-16
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 7 (ASP III)
|Room=APB E007
|Date=2025-12-18
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E008
|Date=2026-01-05
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=CSP
|Room=GÖR/0226/H
|Date=2026-01-06
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 8 (CSP)
|Room=APB E007
|Date=2026-01-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 8 (CSP)
|Room=APB E008
|Date=2026-01-12
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions I
|Room=GÖR/0226/H
|Date=2026-01-13
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 9 (TD I)
|Room=APB E007
|Date=2026-01-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 9 (TD I)
|Room=APB E008
|Date=2026-01-19
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions II
|Room=GÖR/0226/H
|Date=2026-01-20
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 10 (TD II)
|Room=APB E007
|Date=2026-01-22
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo310 (TD II)
|Room=APB E008
|Date=2026-01-26
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Q&A
|Room=GÖR/0226/H
|Date=2026-01-27
|DS=DS2
}}

Advanced Problem Solving and Search (WS2025)

2025-09-22T07:36:49Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Vorlesung |Title=Advanced Problem Solving and Search |Research group=Computational Logic; Logische Programmierung und Argumentation |Lecturers=Sarah Alice Gaggl |Tutors=Sarah Alice Gaggl; Hannes Straß |Term=WS |Year=2025 |Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI |SWSLecture=2 |SWSExercise=2 |SWSPractical=0 |Exam type=nach Mo…“

{{Vorlesung
|Title=Advanced Problem Solving and Search
|Research group=Computational Logic; Logische Programmierung und Argumentation
|Lecturers=Sarah Alice Gaggl
|Tutors=Sarah Alice Gaggl; Hannes Straß
|Term=WS
|Year=2025
|Module=CMS-CE-EL1, CMS-CE-EL2, CMS-CLS-ELG, CMS-CLS-ELV, CMS-COR-FAI, CMS-EE-EL1, CMS-EE-EL2, CMS-VC-ELV2, INF-25-MA-FTK-APSS, INF-BAS2, INF-VERT2, MCL-AI, MCL-KR, MCL-PI
|SWSLecture=2
|SWSExercise=2
|SWSPractical=0
|Exam type=nach Modulbeschreibung
|Description=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
*Evolutionary Algorithms, Genetic Algorithms
*Answer Set Programming
*Constraint Satisfaction Problems
*Structural Decomposition Techniques (Tree/Hypertree Decompositions)

The course does not cover topics in the area of Machine Learning and Neural Networks.

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.

===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 tutorials, the students will analyze different problems and develop solutions for them.

===Prerequisites===
*Basic knowledge of theoretical computer science and Logic.
*Good English skills: teaching will be exclusively in English.

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

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.

Please, register for the course on the OPAL site:

follows soon

===Exam===
Key information:
There are two forms of examination depending on your study program:

Students of the CMS Master, exchange students and students in the Computer Science Master:
*There will be a written exam. Dates and information will follow during the semester. There is no possibility to take the exam remotely.
*You must register in Selma or with your examination office.

Students with complex examinations:
*Please, schedule your oral exams with our secretary (cl@tu-dresden.de) after registering in Selma.
|Literature=*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.
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Introduction
|Room=GÖR/0226/H
|Date=2025-10-14
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Informed vs. Uniformed Search
|Room=GÖR/0226/H
|Date=2025-10-21
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 1 (Traditional Search)
|Room=APB E007
|Date=2025-10-23
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 1 (Traditional Search)
|Room=APB E001
|Date=2025-10-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 1 (Traditional Search)
|Room=APB E008
|Date=2025-10-27
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 1 (Traditional Search)
|Room=APB E001
|Date=2025-09-27
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Local Search
|Room=GÖR/0226/H
|Date=2025-10-28
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 2 (Local Search)
|Room=APB E007
|Date=2025-10-30
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 2 (Local Search)
|Room=APB E008
|Date=2025-11-03
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 2 (Local Search)
|Room=APB E001
|Date=2025-11-03
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Tabu Search
|Room=GÖR/0226/H
|Date=2025-11-04
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 3 (Tabu Search)
|Room=APB E007
|Date=2025-11-06
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 3 (Tabu Search)
|Room=APB E008
|Date=2025-11-24
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 3 (Tabu Search)
|Room=APB E001
|Date=2025-11-24
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Evolutionary Algorithms
|Room=GÖR/0226/H
|Date=2025-11-25
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 4 (EA)
|Room=APB E007
|Date=2025-11-27
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 4 (EA)
|Room=APB E008
|Date=2025-12-01
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 4 (EA)
|Room=APB E001
|Date=2025-12-01
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP I
|Room=GÖR/0226/H
|Date=2025-12-02
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 5 (ASP I)
|Room=APB E007
|Date=2025-12-04
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 5 (ASP I)
|Room=APB E008
|Date=2025-12-08
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 5 (ASP I)
|Room=APB E001
|Date=2025-12-08
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP II
|Room=GÖR/0226/H
|Date=2025-12-09
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 6 (ASP II)
|Room=APB E007
|Date=2025-12-11
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 6 (ASP II)
|Room=APB E008
|Date=2025-12-15
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 6 (ASP II)
|Room=APB E001
|Date=2025-12-15
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=ASP III
|Room=GÖR/0226/H
|Date=2025-12-16
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 7 (ASP III)
|Room=APB E007
|Date=2025-12-18
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 7 (ASP III)
|Room=APB E008
|Date=2026-01-05
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 7 (ASP III)
|Room=APB E001
|Date=2026-01-05
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=CSP
|Room=GÖR/0226/H
|Date=2026-01-06
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 8 (CSP)
|Room=APB E007
|Date=2026-01-08
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 8 (CSP)
|Room=APB E008
|Date=2026-01-12
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 8 (CSP)
|Room=APB E001
|Date=2026-01-12
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions I
|Room=GÖR/0226/H
|Date=2026-01-13
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 9 (TD I)
|Room=APB E007
|Date=2026-01-15
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo3 9 (TD I)
|Room=APB E008
|Date=2026-01-19
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 9 (TD I)
|Room=APB E001
|Date=2026-01-19
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Structural Decompositions II
|Room=GÖR/0226/H
|Date=2026-01-20
|DS=DS2
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Thu1 10 (TD II)
|Room=APB E007
|Date=2026-01-22
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo2 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS4
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo310 (TD II)
|Room=APB E008
|Date=2026-01-26
|DS=DS5
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Übung
|Title=Tutorial Gr-Mo4 10 (TD II)
|Room=APB E001
|Date=2026-01-26
|DS=DS6
}}
{{Vorlesung Zeiten
|Lehrveranstaltungstype=Vorlesung
|Title=Q&A
|Room=GÖR/0226/H
|Date=2026-01-27
|DS=DS2
}}

Thema3514

2025-09-16T11:54:39Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Abschlussarbeit |Titel DE=Explaining Projected Answer Sets Using Faceted Reasoning |Titel EN=Explaining Projected Answer Sets Using Faceted Reasoning |Vorname=Paramita |Nachname=Choudhury |Abschlussarbeitstyp=Master |Betreuer=Sarah Gaggl |Forschungsgruppe=Logische Programmierung und Argumentation |Abschlussarbeitsstatus=Vergeben |Beginn=2025-06-27 |Abgabe=2025-11-28 }}“

Thema3515

2025-09-16T11:52:15Z

Sarah Gaggl:

{{Abschlussarbeit
|Titel DE=Scheduling in Unit-Aware, Batch-Constrained Job Shops Evaluation of Dispatching Rule Strategies and Simulated Annealing Approaches
|Titel EN=Scheduling in Unit-Aware, Batch-Constrained Job Shops Evaluation of Dispatching Rule Strategies and Simulated Annealing Approaches
|Vorname=Tuan Giang
|Nachname=Trinh
|Abschlussarbeitstyp=Master
|Betreuer=Sarah Gaggl
|Partner=Holger Brandl (Systema)
|Forschungsgruppe=Logische Programmierung und Argumentation
|Abschlussarbeitsstatus=Abgeschlossen
|Beginn=2025-02-05
|Abgabe=2025-07-26
}}

Thema3518

2025-09-16T11:50:45Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Abschlussarbeit |Titel DE=Analysis of Runtime Optimization Approaches for Answer Set Programming |Titel EN=Analysis of Runtime Optimization Approaches for Answer Set Programming |Vorname=Pratistha |Nachname=Kansakar |Abschlussarbeitstyp=Master |Betreuer=Sarah Gaggl; Elisa Böhl |Forschungsgruppe=Logische Programmierung und Argumentation |Abschlussarbeitsstatus=Abgeschlossen |Beginn=2025-03-12 |Abgabe=2025-08-26 }}“

{{Abschlussarbeit
|Titel DE=Analysis of Runtime Optimization Approaches for Answer Set Programming
|Titel EN=Analysis of Runtime Optimization Approaches for Answer Set Programming
|Vorname=Pratistha
|Nachname=Kansakar
|Abschlussarbeitstyp=Master
|Betreuer=Sarah Gaggl; Elisa Böhl
|Forschungsgruppe=Logische Programmierung und Argumentation
|Abschlussarbeitsstatus=Abgeschlossen
|Beginn=2025-03-12
|Abgabe=2025-08-26
}}

Thema3515

2025-09-16T11:48:08Z

Sarah Gaggl:

Thema3515

2025-09-16T11:46:05Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Abschlussarbeit |Titel DE=Scheduling in Unit-Aware, Batch-Constrained Job Shops Evaluation of Dispatching Rule Strategies and Simulated Annealing Approaches |Titel EN=Scheduling in Unit-Aware, Batch-Constrained Job Shops Evaluation of Dispatching Rule Strategies and Simulated Annealing Approaches |Vorname=Tuan Giang |Nachname=Trinh |Abschlussarbeitstyp=Master |Betreuer=Sarah Gaggl |Partner=Holger Brandl (Systema) |Forschungsgruppe=Logische Programmierun…“

Inproceedings3432

2025-09-15T10:01:49Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Michelle |ErsterAutorNachname=Kornherr |FurtherAuthors=Augusto B. Correa; Sarah Alice Gaggl; Markus Hecher; Dominik Rusovac; David Speck; Johannes K. Fichte; Daniel Gnad }} {{Inproceedings |Referiert=1 |Title=Graphical Navigation in Solution Spaces using PlanPilot |To appear=1 |Year=2025 |Booktitle=System Demonstrations and Exhibits program at ICAPS 2025 (The 35th International Conference on Automated Plannin…“

{{Publikation Erster Autor
|ErsterAutorVorname=Michelle
|ErsterAutorNachname=Kornherr
|FurtherAuthors=Augusto B. Correa; Sarah Alice Gaggl; Markus Hecher; Dominik Rusovac; David Speck; Johannes K. Fichte; Daniel Gnad
}}
{{Inproceedings
|Referiert=1
|Title=Graphical Navigation in Solution Spaces using PlanPilot
|To appear=1
|Year=2025
|Booktitle=System Demonstrations and Exhibits program at ICAPS 2025 (The 35th International Conference on Automated Planning and Scheduling)
}}
{{Publikation Details
|Abstract=Many planning applications require not only a single solution but benefit substantially from having a set of possible plans from which users can select according to preferences. Surprisingly, planning research has primarily focused on quickly finding single plans for decades. Only recently have researchers started to investigate plan enumeration by top-k planning, offering more flexibility to the user. But simply enumerating the k best plans is far from targeted due to the time-consuming nature of enumeration, likely feeding many similar plans to the user, and forcing the user to define filters beforehand. In fact, in extensive search spaces, enumeration is hardly practical. We present an approach and a tool called PlanPilot to navigate solution spaces of planning tasks iteratively and interactively. We build on answer-set programming (ASP) to restrict the plan space. To that end, we employ facets, which are meaningful actions that appear in some, but not all plans. Enforcing or forbidding such facets allows for navigating even large plan spaces while ensuring desired properties quickly and step by step.
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl}}

Inproceedings3420

2025-08-18T10:02:44Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Daniel
|ErsterAutorNachname=Gnad
|FurtherAuthors=Markus Hecher; Sarah Alice Gaggl; Dominik Rusovac; David Jakob Speck; Johannes K. Fichte
}}
{{Inproceedings
|Referiert=1
|Title=Interactive Exploration of Plan Spaces
|To appear=1
|Year=2025
|Booktitle=KR in the Wild track at KR 2025
}}
{{Publikation Details
|Abstract=Many planning applications require not only a single solution but
benefit substantially from having a set of possible plans from which
users can select, for example, when explaining plans. For
decades, research in classical AI planning has primarily focused on
quickly finding single plans.
Only recently researchers have started to investigate preferences,
enumerate plans by top-k planning, or count plans to reason about
the plan space.
Unfortunately, reasoning about the plan space is computationally
extremely hard and feeding many similar plans to the user is hardly
practical.
To circumvent computational shortcomings while still being able to
reason about variability in plans, faceted actions have been
introduced very recently.
These are meaningful actions that can be used by some plan but are
not required by all plans. Enforcing or forbidding such facets
allows for navigating even large plan spaces while ensuring desired
properties quickly and step by step.
In this paper, we illustrate an industrial challenge, the Beluga
logistics problem of Airbus, where reasoning with facets enables
targeted plan space navigation. We present an approach to handle
large plan spaces iteratively and present a tool that we call planpilot.
|Download=GHGRSF2025-preprint.pdf
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Answer Set Programming
}}

Datei:GHGRSF2025-preprint.pdf

2025-08-18T09:57:38Z

Sarah Gaggl:

Techreport3060

2025-08-18T09:48:01Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Martin
|ErsterAutorNachname=Diller
|FurtherAuthors=Sarah Alice Gaggl; Philipp Hanisch; Giuseppina Monterosso; Fritz Rauschenbach
}}
{{Techreport
|Title=Grounding Rule-Based Argumentation Using Datalog
|Year=2025
|Month=August
|Institution=arXiv.org
|Type=Long version of article to appear in Proceedings of KR 2025
}}
{{Publikation Details
|Abstract=ASPIC+ is one of the main general frameworks for rule-based argumentation for AI. Although first-order rules are commonly used in ASPIC+ examples, most existing approaches to reason over rule-based argumentation only support propositional rules. To enable reasoning over first-order instances, a preliminary grounding step is required. As groundings can lead to an exponential increase in the size of the input theories, intelligent procedures are needed. However, there is a lack of dedicated solutions for ASPIC+. Therefore, we propose an intelligent grounding procedure that keeps the size of the grounding manageable while preserving the correctness of the reasoning process. To this end, we translate the first-order ASPIC+ instance into a Datalog program and query a Datalog engine to obtain ground substitutions to perform the grounding of rules and contraries. Additionally, we propose simplifications specific to the ASPIC+ formalism to avoid grounding of rules that have no influence on the reasoning process. Finally, we performed an empirical evaluation of a prototypical implementation to show scalability.
|Download=DGHMR2025 arxiv.pdf
|Link=https://doi.org/10.48550/arXiv.2508.10976
|DOI Name=https://doi.org/10.48550/arXiv.2508.10976
|Projekt=SECAI, SEMECO-Q1
|Forschungsgruppe=Logische Programmierung und Argumentation, Wissensbasierte Systeme
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Abstrakte Argumentation
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Regelbasiertes Schließen
}}

Techreport3060

2025-08-18T09:47:26Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Martin
|ErsterAutorNachname=Diller
|FurtherAuthors=Sarah Alice Gaggl; Philipp Hanisch; Giuseppina Monterosso; Fritz Rauschenbach
}}
{{Techreport
|Title=Grounding Rule-Based Argumentation Using Datalog
|Year=2025
|Month=August
|Institution=arXiv.org
|Type=To appear in Proceedings of KR 2025
}}
{{Publikation Details
|Abstract=ASPIC+ is one of the main general frameworks for rule-based argumentation for AI. Although first-order rules are commonly used in ASPIC+ examples, most existing approaches to reason over rule-based argumentation only support propositional rules. To enable reasoning over first-order instances, a preliminary grounding step is required. As groundings can lead to an exponential increase in the size of the input theories, intelligent procedures are needed. However, there is a lack of dedicated solutions for ASPIC+. Therefore, we propose an intelligent grounding procedure that keeps the size of the grounding manageable while preserving the correctness of the reasoning process. To this end, we translate the first-order ASPIC+ instance into a Datalog program and query a Datalog engine to obtain ground substitutions to perform the grounding of rules and contraries. Additionally, we propose simplifications specific to the ASPIC+ formalism to avoid grounding of rules that have no influence on the reasoning process. Finally, we performed an empirical evaluation of a prototypical implementation to show scalability.
|Download=DGHMR2025 arxiv.pdf
|Link=https://doi.org/10.48550/arXiv.2508.10976
|DOI Name=https://doi.org/10.48550/arXiv.2508.10976
|Projekt=SECAI, SEMECO-Q1
|Forschungsgruppe=Logische Programmierung und Argumentation, Wissensbasierte Systeme
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Abstrakte Argumentation
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Regelbasiertes Schließen
}}

Datei:DGHMR2025 arxiv.pdf

2025-08-18T09:47:21Z

Sarah Gaggl:

Techreport3060

2025-08-18T09:45:47Z

Sarah Gaggl:

{{Publikation Erster Autor
|ErsterAutorVorname=Martin
|ErsterAutorNachname=Diller
|FurtherAuthors=Sarah Alice Gaggl; Philipp Hanisch; Giuseppina Monterosso; Fritz Rauschenbach
}}
{{Techreport
|Title=Grounding Rule-Based Argumentation Using Datalog
|Year=2025
|Month=August
|Institution=arXiv.org
|Type=To appear in Proceedings of KR 2025
}}
{{Publikation Details
|Abstract=ASPIC+ is one of the main general frameworks for rule-based argumentation for AI. Although first-order rules are commonly used in ASPIC+ examples, most existing approaches to reason over rule-based argumentation only support propositional rules. To enable reasoning over first-order instances, a preliminary grounding step is required. As groundings can lead to an exponential increase in the size of the input theories, intelligent procedures are needed. However, there is a lack of dedicated solutions for ASPIC+. Therefore, we propose an intelligent grounding procedure that keeps the size of the grounding manageable while preserving the correctness of the reasoning process. To this end, we translate the first-order ASPIC+ instance into a Datalog program and query a Datalog engine to obtain ground substitutions to perform the grounding of rules and contraries. Additionally, we propose simplifications specific to the ASPIC+ formalism to avoid grounding of rules that have no influence on the reasoning process. Finally, we performed an empirical evaluation of a prototypical implementation to show scalability.
|Link=https://doi.org/10.48550/arXiv.2508.10976
|DOI Name=https://doi.org/10.48550/arXiv.2508.10976
|Projekt=SECAI, SEMECO-Q1
|Forschungsgruppe=Logische Programmierung und Argumentation, Wissensbasierte Systeme
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Abstrakte Argumentation
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Regelbasiertes Schließen
}}

Techreport3060

2025-08-18T09:44:16Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Martin |ErsterAutorNachname=Diller |FurtherAuthors=Sarah Alice Gaggl; Philipp Hanisch; Giuseppina Monterosso; Fritz Rauschenbach }} {{Techreport |Title=Grounding Rule-Based Argumentation Using Datalog |Year=2025 |Month=August |Institution=arXiv.org |Type=To appear in Proceedings of KR 2025 }} {{Publikation Details |Abstract=ASPIC+ is one of the main general frameworks for rule-based argumentation for AI. Alth…“

{{Publikation Erster Autor
|ErsterAutorVorname=Martin
|ErsterAutorNachname=Diller
|FurtherAuthors=Sarah Alice Gaggl; Philipp Hanisch; Giuseppina Monterosso; Fritz Rauschenbach
}}
{{Techreport
|Title=Grounding Rule-Based Argumentation Using Datalog
|Year=2025
|Month=August
|Institution=arXiv.org
|Type=To appear in Proceedings of KR 2025
}}
{{Publikation Details
|Abstract=ASPIC+ is one of the main general frameworks for rule-based argumentation for AI. Although first-order rules are commonly used in ASPIC+ examples, most existing approaches to reason over rule-based argumentation only support propositional rules. To enable reasoning over first-order instances, a preliminary grounding step is required. As groundings can lead to an exponential increase in the size of the input theories, intelligent procedures are needed. However, there is a lack of dedicated solutions for ASPIC+. Therefore, we propose an intelligent grounding procedure that keeps the size of the grounding manageable while preserving the correctness of the reasoning process. To this end, we translate the first-order ASPIC+ instance into a Datalog program and query a Datalog engine to obtain ground substitutions to perform the grounding of rules and contraries. Additionally, we propose simplifications specific to the ASPIC+ formalism to avoid grounding of rules that have no influence on the reasoning process. Finally, we performed an empirical evaluation of a prototypical implementation to show scalability.
|Link=https://doi.org/10.48550/arXiv.2508.10976
|DOI Name=https://doi.org/10.48550/arXiv.2508.10976
|Forschungsgruppe=Logische Programmierung und Argumentation, Wissensbasierte Systeme
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Abstrakte Argumentation
}}
{{Forschungsgebiet Auswahl
|Forschungsgebiet=Regelbasiertes Schließen
}}

Inproceedings3422

2025-08-11T07:09:22Z

Sarah Gaggl: Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorVorname=Daniel |ErsterAutorNachname=Gnad |FurtherAuthors=Augusto B. Correa; Johannes K. Fichte; David Speck; Dominik Rusovac; Sarah Alice Gaggl; Markus Hecher }} {{Inproceedings |Referiert=1 |Title=PlanPilot: Efficient Navigation in Plan Space |To appear=0 |Year=2025 |Month=August |Booktitle=Workshop on Explainable Artificial Intelligence (XAI) }} {{Publikation Details |Abstract=Many planning applications require not…“

{{Publikation Erster Autor
|ErsterAutorVorname=Daniel
|ErsterAutorNachname=Gnad
|FurtherAuthors=Augusto B. Correa; Johannes K. Fichte; David Speck; Dominik Rusovac; Sarah Alice Gaggl; Markus Hecher
}}
{{Inproceedings
|Referiert=1
|Title=PlanPilot: Efficient Navigation in Plan Space
|To appear=0
|Year=2025
|Month=August
|Booktitle=Workshop on Explainable Artificial Intelligence (XAI)
}}
{{Publikation Details
|Abstract=Many planning applications require not only a single solution but benefit substantially from having a set of possible plans from which users can select according to preferences. Surprisingly, planning research has primarily focused on quickly finding single plans for decades. Only recently have researchers started to investigate plan enumeration by top-k planning, offering more flexibility to the user. But simply enumerating the k best plans is
far from targeted due to the time-consuming nature of enumeration, likely feeding many similar
plans to the user, or forcing the user to define filters beforehand. In fact, in extensive search spaces, enumeration is hardly practical. We present an approach and a tool called PlanPilot to navigate solution spaces of planning tasks iteratively and interactively. We build on answer-set programming (ASP) to restrict the plan space. To that end, we employ facets, which are meaningful actions that appear in some, but not all plans. Enforcing or forbidding such facets allows for navigating even large plan spaces while ensuring desired properties quickly and step by step.
|Download=Facet reason xai2025 crc.pdf
|Forschungsgruppe=Logische Programmierung und Argumentation
}}
{{Forschungsgebiet Auswahl}}

Datei:Facet reason xai2025 crc.pdf

2025-08-11T07:08:41Z

Sarah Gaggl: