Single-Course English 7.5 ECTS

Artificial Intelligence and Multi-Agent Systems

Overall Course Objectives

This course introduces students to advanced techniques within artificial intelligence (AI), with particular focus on automated planning and multi-agent systems. The objective of the course is to become able to explain, analyse and implement advanced AI techniques.

Learning Objectives

  • describe a number of the most prevalent techniques in artificial intelligence – both in overall terms and on a detailed technical level
  • compare and assess the appropriateness of various AI techniques for solving a given concrete problem
  • combine different AI techniques in a theoretically sound and practically useful way
  • apply a given AI technique to a given concrete problem
  • clarify the general complications and pitfalls involved in practical uses of AI techniques
  • independently explore the literature relevant to a specific AI project
  • implement non-trivial AI techniques in a relatively large software system
  • communicate results within the areas of the course in the style of a research conference contribution

Course Content

The course primarily focuses on topics within automated planning and multi-agent systems, but will also address other areas of AI (e.g. problem-solving by searching, knowledge representation and reasoning with logical agents).

The programming project concerns the design and implementation of advanced AI techniques in a simulated multiagent environment. The programming project is very open-ended and invites for the development of your own algorithms and multiagent architectures. The project is carried out in groups, and should result in a working system and a video in which you present the system and its underlying ideas in the style of research presentations at AI conferences.

In addition to the programming project there will be 2 smaller assignments during the course.

Recommended prerequisites

01017/02101/02105/02180/02156, or equivalent courses, including knowledge about graph search algorithms, search heuristics and predicate logic. Furthermore, the course requires experience with implementing non-trivial algorithms and larger software systems.

Teaching Method

Lectures, exercises, assignments and a large programming project.


See course in the course database.





13 weeks




DTU Lyngby Campus

Course code 02285
Course type Candidate
Semester start Week 5
Semester end Week 19
Days Tues 13-17

11.250,00 DKK