Artificial Intelligence and Multi-Agent Systems

• describe a number of the most prevalent techniques in artificial intelligence and multi-agent systems – both in overall terms and on a detailed technical level
• compare and assess the appropriateness of various AI techniques within automated planning and multi-agent systems 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 within automated planning and multi-agent systems
• 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

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 smaller assignments during the course.

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

Lectures, exercises, assignments and a large programming project.