
Department of
Computational Perception


Artificial Intelligence
344.014, VO, 2 hrs. (3 ECTS), WS 2017/18
Univ.Prof. Dr. Gerhard Widmer
This class will be taught in English.
TIME: Monday, 12:00  13:30
START: Monday, Oct. 2, 2017
PLACE: HS 19 (Informatics Building  Science Park III)
Goals and Contents of this Class:
The lecture gives an introduction to basic models and techniques in the
field of Artificial Intelligence (AI). Specific topics to be covered include:
 Definitions of AI, history of AI, current state of the field
 Motivating scenario: autonomous intelligent "agents"
 Problem solving as a search process:
 uninformed search algorithms
 heuristic search algorithms
 heuristic search in game playing
 Knowledge representation and logical inference:
 Propositional logic
 Firstorder (predicate) logic
 Logic as a programming language: PROLOG
 Representing and reasoning with uncertain knowledge:
 Basics of Bayesian probability theory
 Knowledge representation and inference in Bayesian networks
 Basic notions of machine learning:
 Learning logical definitions: inductive concept learning
 Learning strategies for intelligent action: reinforcement learning
 Basic notions of computer perception
Teaching materials:
Pdf versions of the Powerpoint slides used in the lecture will be made
available via KUSSS (weekly).
Recommended reading (will not be needed if the lectures are
attended on a regular basis):
Russell, S.J. and Norvig, P. (2000).
Artificial Intelligence: A Modern Approach (2nd. Edition).
Englewood Cliffs, NJ: PrenticeHall.
Exercise track (Übung):
The class is accompanied by an
exercise track (344.021, 344.022, 344.023),
in which the students will improve their understanding of the material
by solving a series of theoretical and practical examples.
Be sure to also register for one of 344.021, 344.022, 344.023!
Questions, suggestions, complaints, etc. to:
Gerhard Widmer
Tel. 24684701
gerhard dot widmer at jku dot at
last edited by gw on Aug 16, 2017