Game theory and social choice

Students who do exceptionally well in the midterm examination will have the option to write a paper in lieu of the final. Computer Science Fall For full functionality of this site it is necessary to enable JavaScript. Here are the instructions how to enable JavaScript in your web browser. Bidding languages. Note: we won't go in the same order as the book in the next few lectures. I'm pointing out the chapters that are associated with each lecture, but for reading purposes you may prefer following the order of the book for the next few lectures, reading mechanism design Ch.

SLB Optional: Lehmann et al. Sandholm chapter on optimal winner determination. Analyzing auction mechanisms: Bayesian games, Bayes-Nash equilibrium, revenue equivalence, revenue-maximizing Myerson auctions, redistribution auctions. SLB 6. Article on swoopo. Mechanism design. Incentive compatibility. Individual rationality. Revelation principle. Clarke mechanism. Generalized Vickrey Auction. Groves mechanisms. Myerson-Satterthwaite impossibility.

Computational topics. Chapter Optional: rest of chapter Parkes chapter on mechanism design. Practice midterm. Just in case we have some extra time during the review or in case you're interested after : practice questions: ppt , pdf. Meanwhile please watch assigned video.

Optional: Paper on computing a Nash equilibrium in repeated games. How do separated agents succeed in coordinating their actions so that the formal outcome is the result of each agent's rational choice? In social interaction, rationality has to be enriched with further assumptions about individuals' mutual knowledge and beliefs, but these assumptions are not without consequence.

Cristina Bicchieri has been working on the epistemic foundations of game theory, analyzing the consequences of relaxing the 'common knowledge' assumption in several classes of games. Her contributions include axiomatic models of players' theory of the game and the proof that -- in a large class of games -- a player's theory of the game is consistent only if the player's knowledge is limited.

An important consequence of assuming bounded knowledge is that it allows for more intuitive solutions to familiar games such as the finitely repeated prisoner's dilemma or the chain-store paradox.

Bicchieri has also been interested in devising mechanical procedures algorithms that allow players to compute solutions for games of perfect and imperfect information. Devising such procedures is particularly important for Artificial Intelligence applications, since interacting software agents have to be programmed to play a variety of 'games'.

Learning and belief revision are important elements of what we mean by rationality.