MA437 Half Unit
Learning Dynamics in Games
This information is for the 2025/26 session.
Course Convenor
Prof Bernhard Von Stengel
Dr Galit Ashkenazi-Golan
Availability
This course is available on the MSc in Mathematics and Computation and MSc in Operations Research & Analytics. This course is available with permission as an outside option to students on other programmes where regulations permit. This course uses controlled access as part of the course selection process.
In case the cap is reached, the lecturers will prioritise access according to interest, background, and fit with study plans such as planned dissertations of participants.
Requisites
Pre-requisites:
Students must have completed MA301 before taking this course.
Course content
Multiagent learning dynamics and their challenges.
Fictitious play, replicator dynamics, projected gradient, Q-learning, learning with neural networks.
Convergence and limit behaviour, reachable types of equilibria (Nash, correlated, coarse correlated), relation to game types such as zero-sum or potential games.
Teaching
20 hours of lectures and 10 hours of seminars in the Winter Term.
The first five seminars will involve exercises and formative presentation rehearsals. The second five seminars will involve exercises and summative presentations.
Formative assessment
Problem sets will be set and marked and discussed in the seminars, where students will also have the opportunity to first rehearse giving presentations. Later in the seminars, each student will give a summatively assessed presentation.
Indicative reading
Reading materials will be provided on the Moodle page of the course.
Assessment
Exam (75%), duration: 120 Minutes in the Spring exam period
Project (25%) in Winter Term Week 6
The presentation will be accompanied by a short written report.
The presentation and report combined account for 25% of the mark.
The written exam accounts for 75%.
Key facts
Department: Mathematics
Course Study Period: Winter Term
Unit value: Half unit
FHEQ Level: Level 7
Keywords: Game Theory, Machine Learning, Artificial Intelligence, Learning Dynamics
Total students 2024/25: Unavailable
Average class size 2024/25: Unavailable
Controlled access 2024/25: NoCourse selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Leadership
- Self-management
- Team working
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills