Problem Solving and Search in Artificial Intelligence

From International Center for Computational Logic

Problem Solving and Search in Artificial Intelligence

Course with SWS 2/2/2 (lecture/exercise/practical) in SS 2020

Lecturer

Tutor

SWS

  • 2/2/2

Modules

Examination method

  • Oral exam

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

The course covers the following topics:

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


Learning Outcomes

  • The students should identify why typical AI problems are difficult to solve
  • The students will analyze different algorithms and methods for AI problems and identify when their application is appropriate
  • The connections between the (graph) structure and the complexity of a problem should become clear, as well as which methods can be used to tackle the problem
  • In the practical part, the students will analyze a given problem and develop a solution for it.

Prerequisites

Basic knowledge of theoretical computer science and Logic.

Organisation

The goals can be acquierd by studying the lecture material, solving the exercises of the tutorials and developing an implementation for a practical problem.

The practical work should be performed in groups of two students throughout the semester with regular updates on the progress.

The lecture will be on Tuesday DS2 and the tutorials on Thursday DS1. Please check the concrete schedule for changes.

Announcement: because of the COVID-19 pandemic we will provide the materials for self-learning on the planed dates for lectures and tutorials. Please register for the course in OPAL:

https://bildungsportal.sachsen.de/opal/auth/RepositoryEntry/23291363328
  • 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.

Subscribe to events of this course (icalendar)

Lecture Introduction DS2, April 14, 2020 in APB E005 Download Download Download
Lecture Informed vs. Uninformed Search DS1, April 16, 2020 in APB E005 Download Download
Lecture Local Search DS2, April 21, 2020 in APB E005 Download Download Download
Exercise Tutorial 1 (Local Search) DS1, April 23, 2020 in APB E005 Download Download Download
Lecture Tabu Search DS2, April 28, 2020 in APB E005 Download Download
Practical Practical Work Topic DS2, April 28, 2020 in APB E005 Download Download
Exercise Tutorial 2 (Tabu Search) DS1, April 30, 2020 in APB E005 Download Download Download Download
Lecture ASP 1 DS2, May 5, 2020 in APB E005 Download Download Download
Exercise Tutorial 3 (ASP 1) DS1, May 7, 2020 in APB E005 Download Download
Lecture ASP 2 DS2, May 12, 2020 in APB E005 Download Download Download
Exercise Tutorial 4 (ASP 2) DS1, May 14, 2020 in APB E005 Download
Practical Practical Work Discussion DS1, May 15, 2020 in APB E005
Lecture ASP 3 DS2, May 19, 2020 in APB E005 Download Download Download
Lecture CSP DS2, May 26, 2020 in APB E005 Download Download
Exercise Tutorial 5 (CSP) DS1, May 28, 2020 in APB E005 Download Download
Lecture Evolutionary Algorithms DS2, June 9, 2020 in APB E005 Download
Exercise Tutorial 6 (EA 1) DS1, June 11, 2020 in APB E005
Lecture Structural Decompositions 1 DS2, June 16, 2020 in APB E005
Exercise Tutorial 7 (EA 2) DS1, June 18, 2020 in APB E005
Lecture Structural Decompositions 2 DS2, June 23, 2020 in APB E005
Exercise Tutorial 8 (Structural Decompositions) DS1, June 25, 2020 in APB E005
Practical Practical Work Presentations DS2, June 30, 2020 in APB E005
Exercise Tutorial 9 DS1, July 2, 2020 in APB E005
Lecture Q&A DS2, July 7, 2020 in APB E005
Exercise Tutorial 10 DS1, July 9, 2020 in APB E005
Practical Practical Work DS2, July 14, 2020 in APB E005
Exercise Tutorial 11 DS1, July 16, 2020 in APB E005


Calendar