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Dr Galit Ashkenazi-Golan COL 3.08

This course is available on the BSc in Accounting and Finance, BSc in Data Science, BSc in Econometrics and Mathematical Economics, BSc in Economics, BSc in Management, BSc in Mathematics and Economics, BSc in Mathematics with Data Science, BSc in Mathematics with Economics, BSc in Mathematics, Statistics and Business and BSc in Psychological and Behavioural Science. This course is available as an outside option to students on other programmes where regulations permit. This course is available with permission to General Course students.

Familiarity with a rigorous treatment of mathematics (through definitions, theorems and proofs) is expected. Basic knowledge of matrices and continuity as covered in Mathematical Methods (MA100) or Quantitative Methods (MA107) as well as some knowledge of probability is required.

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.

This course is delivered through a combination of classes and lectures totalling a minimum of 30 hours across Autumn Term.

Written answers to set problems will be expected on a weekly basis.

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

Exam (90%, duration: 2 hours) in the January exam period.
Continuous assessment (10%).