Game Theory

Game Theory

Credits

6

Prerequisites

Numerical Computing and Programming.

Examination method

Final assessment by means of written and/or oral exams.

Learning
objectives

The aim of the course is to provide the conceptual and formal tools useful for modelling (and sometimes solving) economic (and other) situations in which several decision-makers interact, that is, situations in which the payoff received by a decision-maker depends not only on their own choice but also on those of the others.

Contents

Finite games in extensive form Game tree. Perfect or imperfect information, perfect or imperfect recall. Pure, mixed and behavioural strategies. Subgames.
2. Non-cooperative games in normal form (finite or infinite). Passing from the extensive form to the normal form. Concepts of dominance. Best responses of a player. Maximin (prudent) solutions. Nash equilibria: existence (Nash’s theorem), characterisations and properties. The case of zero-sum games. Methods for determining Nash equilibria. Cournot model for duopoly markets.
3. Selection of Nash equilibria in finite non-cooperative games in extensive form. Incomplete information: Bayesian Nash equilibrium. Perfect information: subgame-perfect Nash equilibrium. Stackelberg model for duopoly markets.

Academic Year
2018/2019

Lecturer: Achille BASILE.

Semester: first.

Syllabus: see the dedicated page.