Intelligent Systems


Course Objective

This course gives an overview over the theory and practice of
Intelligent Systems, systems that perceive, reason, learn, and act
Students will acquire practical skills in developing intelligent systems
building on a thorough understanding of well-understood Artificial
Intelligence approaches, including Knowledge Representation and Machine

Course Content

The course will provide an in-depth understanding of classical AI
problems and approaches, such as search, knowledge representation,
machine learning, etc., by deepening the theoretical understanding and
ability to apply those techniques in practice.

Teaching Methods

The course will be centered on the practical task of designing
intelligent agents that perform in a challenging competition against
other agents.
There will be 12 lectures in the first 3 weeks, as well as a number of
practical sessions in a lab, working groups to help with the course
material and a significant amount of self-study, both to
familiarise oneself with the AI theory and methods, and to program an
Intelligent System using those methods.

Method of Assessment

There will be an exam (probably digital) and a groups assignment.


Russell, Norvig: Artificial Intelligence: A Modern Approach. Most recent
Edition. Recommended, but not compulsory. There will be a reader.

Target Audience

2CS, 2LI, 2IMM

General Information

Course Code X_401086
Credits 6 EC
Period P3
Course Level 200
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. K.S. Schlobach
Examiner dr. K.S. Schlobach
Teaching Staff dr. K.S. Schlobach

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar, Lecture, Practical
Target audiences

This course is also available as: