Introduction Artificial Intelligence A

Teaching methods

Lectures, question-and-answer seminars and practice sessions.


Some knowledge of mathematics, programming and formal logic is beneficial.


The overall learning aims of the course are that students will be able to:

  • Recognise typical AI problems, explain typical features of AI problems and think up examples of AI problems.
  • Explain the relationship between a problem space and a search tree, explain fundamental search methods and their differences, produce an algorithm in pseudo code for elementary search techniques and select and apply search techniques in basic examples.
  • Cite examples of different types of knowledge representation and produce effective types of representation for basic examples.
  • Explain the methods for solving constraint satisfaction problems, and use them in basic examples.
  • Explain the essence of different learning methods and elaborate on the details of these methods in basic examples.


The aim of the course is to give students a first impression of the field of Artificial Intelligence, without going into too much technical detail. The course will cover:

  • What Artificial Intelligence is and an example of how AI techniques can be applied to an existing software system.
  • Fundamental search techniques and their application.
  • Types of knowledge representation, the main languages which are used and an example of their application in the field of Artificial Intelligence.
  • Constraint satisfaction problems.
  • Learning through computers, the main techniques which are used and an example of their application.


The following book is compulsory for AI students and is recommended for Computer Science students:

  • Poole, D.I.R. & Mackworth, A.K.P. Artificial Intelligence: Foundations of Computational Agents. Cambridge University Press, 2010, ISBN 978-0-521-51900-7.
    (The entire book is legitimately available via

Course ID
4 ec
1st semester
Show schedule
SWS / PersoonlijkRooster


Included in