Introduction This lecture focuses on the interpretation of solution concepts for normal-form games. You will recall that, when we introduced Nash equilibrium and Rationalizability, we mentioned numerous reasons why these solution concepts could be regarded as yielding plausible restric- tions on rational play, or perhaps providing a consistency check for our predictions about
Introduction This lecture, as well as the next, exemplify applications of the framework and techniques developed so far to problems of economic interest. Neither lecture attempts to cover the example applications in any generality, of course; you may however find these topics of sufficient interest to warrant further study Auction theory is generally indicated as one of the \success stories\of game theory There is no doubt that the game-theoretic analysis of auctions has informed design decisions
Introduction One of the merits of the notion of sequential equilibrium is the emphasis on out-of- equilibrium beliefs-that is, on beliefs (about past and future play)at information sets that should not be reached if given equilibrium is played. The key insight of extensive-form analysis is that out-of-equilibrium beliefs deter
Introduction: Invariance In their seminal contribution, Von Neumann and Morgenstern argue that the normal form of a game contains all\strategically relevant\information. This view, note well, does not invalidate or trivialize extensive-form analysis; rather, it leads those who embrace it to be uspicious of extensive-form solution concepts which yield different predictions in distinct
Player i is rational\;R=nieN Ri. Also, Bi(E) is the event \Player i is certain that E is true\ and B(E)=neN Bi(E). This is as in Lecture 7. Let me introduce the following notation for iterated mutual certainty: B()(E)=E B()(E)=B(B-I)(E)). Then the definition of Bk in Lecture 7 can be rewritten as Bk
1. Machines Extend Proposition 151. 1(the Perfect Folk Theorem with discounting)to arbitrary mixtures of payoff profiles of the original game G=(N, (Ai, lilieN Allow for both rational and real weights on the set of profiles u(a): aE A]; note that the statement of the result will involve an approximation of the payoff profile Construct a machine that implements the strategies in your proof
