CPSC 767: Advanced Topics in Multi-Agent Systems


Jörg Denzinger
Email: denzinge@cpsc.ucalgary.ca Phone: (403) 220-5574
Office: ICT 752

General Information

This course is intended for students who already have basic knowledge about multi-agent systems (and/or AI) and who want to learn more about the state-of-the-art in a specific subfield of multi-agent systems (or AI). The format of the course is in the form of a project. Each student is given a subfield of multi-agent systems (or AI) and, if necessary, a particular application area for concepts from the subfield (if the subfield as a whole is too big). Then the student has to do research on the given subfield and its application. He or she has to produce a report that provides an overview of the subfield and its concepts structured in the form of classification dimensions (or questions to answer) for works in the area. Also, each student has to give a presentation in which he/she presents the results of the project.

The prerequisite for this course is that a student has taken either CPSC 609 or CPSC 567 (or has otherwise sufficient knowledge in MAS and/or AI) and that he/she has my permission. For the later, I suggest that a student who is interested in the course contacts me to discuss a possible subfield and a particular application.

Note that 767 is usually not offered without having at least one student who wants to take it. Therefore, please contact me if you are interested even if 767 is not showing up in PeopleSoft.


The University policy on grading and related matters is described in the university calendar and naturally this policy is also applied to this course. Course specific details are as follows.

A student has to give a presentation on the status of the project to the supervisor and has to produce the report, which are both based on the developed classification dimensions. Consequently, the course grade will combine a grade for the developed classification dimensions (as demonstrated by report and presentation), the report and the presentation. The weighting of these grades is as follows:

Dimensions        40%
Report        30%
Presentation        30%

Last Change: 16/5/2019