Module Number

Module Title

Artificial Intelligence
Type of Module

Elective Compulsory
Work load
- Contact time
- Self study
180 h
Class time:
60 h / 4 SWS
Self study:
120 h
Duration 1 Semester
Frequency In the winter semester
Language of instruction German and English
Type of Exam

Written Test

Lecture type(s) Lecture

The module covers approximately the first half of the book by Stuart Russel, Peter Norvig: Artificial Intelligence, A Modern Approach, 3rd. Edition. This includes: Introduction, Foundations and History of AI, Intelligent Agents, Problem Solving by Search, Heuristic Search Methods, Local Search Methods, Searches with Nondeterministic Actions and Partial Observations, Search Methods with Adversaries (Adversarial Search), Search Methods for Games, Alpha Beta Pruning, Stochastic Games, Constraint satisfaction problems, Backtracking search, Logical agents, Agents based on propositional logic, Predicate logic and knowledge representation in it, Unification and lifting, Forward chaining, Backward chaining, Prolog, Classical planning, Hierarchical planning and multiagent planning, Knowledge representation. The concepts of the lecture are deepened in exercises and programming tasks with Lisp or Java . Students learn to solve problems with AI techniques independently. solve problems.


Students will have basic knowledge of artificial intelligence based on the most internationally known AI textbook by Russel/Norvig.

Allocation of credits / grading
Type of Class
Type of Exam
Exam duration
of Module (%)
Prerequisite for participation There are no specific prerequisites.
Lecturer / Other Zell

Skriptum zur Vorlesung, und Lehrbuch S. Russel, P. Norvig: Artifi- cial Intelligence: A Modern Approach, 3rd Edition, Pearson

Last offered Wintersemester 2022
Planned for Wintersemester 2023
Assigned Study Areas BIOINFM2510, INFM2510, INFM3110, INFM3410, MDZINFM2510, MEINFM3210