MA413      Half Unit
Games of Incomplete Information

This information is for the 2018/19 session.

Teacher responsible

Dr Robert Simon COL 4.07

Availability

This course is available on the MSc in Applicable Mathematics. This course is available with permission as an outside option to students on other programmes where regulations permit.

Pre-requisites

Students should be familiar with the related mathematics of topology and functional analysis. Some degree of mathematical maturity is expected.

Course content

The techniques and results of game theory are increasingly important to economic analysis. This course focuses on the problems of information incompleteness and information asymmetry. This is a relatively new but rapidly expanding area of game theory with connections to several areas of economic theory, for example conflict resolution, auctions, principal-agent problems, and the logic of knowledge. The course is divided into three parts, I Basic Results, II Repeated Games, III Bayesian Games. For the first part we cover the Min-max Theorem and Nash's Theorem of Equilibrium Existence, Extensive Form and Discounted Games.  For the second part we cover Zero-sum Games with Vector Payoffs, The Value of the Zero-sum Repeated Game of Incomplete Information on One Side, Non-Zero-Sum Games with Incomplete Information on One Side. For the third part we cover Common Knowledge, Zero-Sum Bayesian Games, Locally Finite Games, and Non-Zero-Sum Bayesian Games.

Teaching

22 hours of lectures and 10 hours of seminars in the LT.

Formative coursework

Weekly exercises are set and marked.

Indicative reading

A full set of lecture notes will be provided. Useful accompanying texts are Robert J. Aumann and Michael B. Maschler, Repeated Games with Incomplete Information, MIT Press, 1995; L. Breiman, Probability; K. Border, Fixed Point Theorems with Applications to Economics and Game Theory; R Myserson, Game Theory, Analysis of Conflict, Harvard University Press; D Fudenberg & J Tirole, Game Theory, MIT Press.

Assessment

Exam (100%, duration: 2 hours) in the summer exam period.

Key facts

Department: Mathematics

Total students 2017/18: 11

Average class size 2017/18: 11

Controlled access 2017/18: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

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