MA402      Half Unit
Mathematical Game Theory

This information is for the 2025/26 session.

Course Convenor

Dr Galit Ashkenazi-Golan

Prof Bernhard Von Stengel

Availability

This course is available on the CEMS Exchange, MBA Exchange, MPA in Data Science for Public Policy, MSc in Financial Mathematics, MSc in Mathematics and Computation and MSc in Operations Research & Analytics. This course is freely available as an outside option to students on other programmes where regulations permit. It does not require permission.

It is not available to students who have taken Game Theory I (MA301).

Students on the MPA in Data Science for Public Policy are required to seek permission to take this course. 

Requisites

Additional requisites:

Familiarity with a rigorous treatment of mathematics (through definitions, theorems and proofs) is expected. Students must know basics of linear algebra (matrix multiplication, geometric interpretation of vectors), analysis (continuity, closed sets), and probability theory (expected value, conditional probability, independence of random events).

Course content

Concepts and methods of mathematical game theory. Nim and combinatorial games. Congestion games. Games in strategic form, dominated strategies, Nash equilibrium. Cournot quantity competition. Game trees with perfect information, backward induction. Commitment. Expected utility. Mixed equilibrium. Zero-sum games, maxmin strategies. Extensive games with information sets, behaviour strategies, perfect recall. Bargaining. Geometry of equilibria.

Teaching

10 hours of seminars and 20 hours of lectures in the Autumn Term.

Formative assessment

Weekly exercises are set and marked.

 

Indicative reading

Required text: B von Stengel, Game Theory Basics. Cambridge University Press, 2022.

Assessment

Exam (90%), duration: 120 Minutes in the January exam period

Continuous assessment (10%)


Key facts

Department: Mathematics

Course Study Period: Autumn Term

Unit value: Half unit

FHEQ Level: Level 7

CEFR Level: Null

Total students 2024/25: 33

Average class size 2024/25: 17

Controlled access 2024/25: No
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Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills