MA330      Half Unit
Game Theory for Collective Decisions

This information is for the 2025/26 session.

Course Convenor

Dr Galit Ashkenazi-Golan

Availability

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, BSc in Psychological and Behavioural Science, Erasmus Reciprocal Programme of Study and Exchange Programme for Students from University of California, Berkeley. This course is freely available as an outside option to students on other programmes where regulations permit. It does not require permission. This course is available with permission to General Course students.

Requisites

Additional requisites:

Familiarity with a rigorous treatment of mathematics (through definitions, theorems and proofs) is expected. Basic knowledge of matrices as covered in Mathematical Methods (MA100) or Quantitative Methods (MA107) as well as some knowledge of probability is required. Recommended: MA301 Mathematical Game Theory, otherwise with approval from the MA330 lecturer.

Course content

Coalitional game theory - central solution concepts and applications to economics: games with transferable utility, the Core, Shapley value, market games, social choice, stable matching.

Teaching

20 hours of lectures and 10 hours of classes in the Winter Term.

Formative assessment

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

 

Indicative reading

Lecture notes will be provided, as well as references to selected papers. Further reading: M Maschler, E Solan, S Zamir: Game Theory, Cambridge University Press 2020.

Assessment

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

Continuous assessment (10%)


Key facts

Department: Mathematics

Course Study Period: Winter Term

Unit value: Half unit

FHEQ Level: Level 6

CEFR Level: Null

Total students 2024/25: 25

Average class size 2024/25: 25

Capped 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