Algorithmic Game Theory BAI405D
Course Code: BAI405D
Credits: 03
CIE Marks: 50
SEE Marks: 50
Total Marks: 100
Exam Hours: 03
Total Hours of Pedagogy: 40H
Teaching Hours/Weeks: [L:T:P:S] 2:2:0:0
Introduction to Strategic Games: What is game theory? The theory of rational choice, Strategic games; Examples: The prisoner’s dilemma, Bach or Stravinsky, Matching pennies; Nash equilibrium; Examples of Nash equilibrium; Best response functions; Dominated actions.
Introduction: Strategic games in which players may randomize; Mixed strategy Nash equilibrium; Dominated actions; Pure equilibrium when randomization is allowed. Illustration: Expert Diagnosis; Equilibrium in a single population.
Extensive games with perfect information: Strategies and outcomes; Nash equilibrium; Subgame perfect equilibrium; Finding sub-game perfect equilibria of finite horizon games: Backward induction; Illustrations: The ultimatum game, Stackelberg’s model of duopoly.
Bayesian Games: Motivational examples; General definitions; Two examples concerning information; Illustrations: Cournot’s duopoly game with imperfect information, Providing a public good; Auctions: Auctions with an arbitrary distribution of valuations.
Competitive Games: Strictly competitive games and maximization. Repeated games: The main idea; Preferences; Repeated games; Finitely and infinitely repeated Prisoner’s dilemma; Strategies in an infinitely repeated Prisoner’s dilemma; Nash equilibrium of an infinitely repeated Prisoner’s dilemma, Nash equilibrium payoffs of an infinitely repeated Prisoner’s dilemma.