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Artificial Intelligence 1

The course "Artificial Intelligence 1" provides an overview on basic approaches of artificial intelligence within the areas of search, planning, knowledge representation, reasoning, and multi agent systems. The aim of this course is to teach foundational principles of symbolic AI approaches, its connections to logic, and basic formalisation aspects. The theoretical concepts taught in the lecture will be accompanied by practical programming exercises with Prolog. The contents of this course are as follows

  1. Introduction
  2. Classical Logics and Prolog
    1. Classical logics
    2. Prolog
  3. Search and Automatic Planning
    1. Uninformed search
    2. Informed search
    3. Situation calculus and STRIPS
  4. Knowledge Representation and Reasoning
    1. Default logic
    2. Answer set programming
    3. Formal argumentation
    4. Belief revision
  5. Agents and Multi Agent Systems
    1. Agent models
    2. Multi agent logics
  6. Summary and Conclusion


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  • Mondays 10:15-11:45 in E.314
  • No lecture on May 21 (Pfingsten)


  • Thursdays 14:15-15:45 in F.314
  • No tutorials on May 10, May 24, and May 31 (Christi Himmelfahrt, Pfingsten, Fronleichnam)




Exercise sheets:


Additional material:


Please acknowledge the following guidelines to obtain the credits for this course:

  • In order to obtain the credits of this course (6 ECTS), you have to obtain admission to take part in the exam and pass the exam.
  • Admission to the exam is granted to all students who achieve 60% of the score obtainable in the exercises of the tutorials and to all students who already gained admission to the exam in 2015, 2016, or 2017.
  • Active participation in the tutorials is expected.
  • Obligation to to register for the exam
    • There is an obligation to register for the exam.
    • If someone is not correctly registered for the exam before end of the corresponding deadline, he or she cannot participate in the exam.
    • If someone is registered for the exam but does not show up, he or she will fail the exam.
  • If you fail the (written) exam has to do a retake within the next 6 months; this second (or third) exam is orally and has to be scheduled with the lecturer in person.

Tutorials structure



The following textbooks are recommended:

  • Stuart Russell, Peter Norvig: Artificial Intelligence: A Modern Approach
    Third Edition, Prentice Hall, 2010
  • Christoph Beierle, Gabriele Kern-Isberner: Methoden wissensbasierter Systeme
    Vierte Auflage, Vieweg+Teubner, 2008 (in German)
  • Ronald Brachman, Hector Levesque: Knowledge Representation and Reasoning
    First Edition, Morgan Kaufmann Series, 2004
  • Gerhard Weiss (Editor): Multiagent Systems
    Second Edition, MIT Press, 2013

Course in KLIPS: Lecture, Tutorials