Games of Incomplete Information

**This information is for the 2019/20 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, Repeated Game of Incomplete Information on One Side, and myopic equilibria. For the third part we cover Common Knowledge, Zero-Sum Bayesian Games, Locally Finite Games, and Non-Zero-Sum Bayesian Games.**Teaching**

20 hours of lectures and 10 hours of seminars in the LT. 2 hours of lectures in the ST.

**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 2018/19: 4

Average class size 2018/19: 4

Controlled access 2018/19: No

Value: Half Unit

**Personal development skills**

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