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
Dept. of Electrical Computer Engineering OOCL Transportation Co Dept, of Economics University of Ilinois at Urbana-Champaign 300 Central Ave Urbana IL 6180 University of Illinois at Urbana-Champaign Mountain view, CA 94043 Champaign, IL 61820 Abstract We provide a brief review of the EWPP operation [1].The Pool dispatcher is charged with determining on a daily basis We formulate a general framework of a competitive electric- the schedule for the so-called availability declaration period ity generation supply market(CEM, embodying the salient (ADP),a 39-bour
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
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
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
NOTE: On the“ ethics” of problem sets Some of the theoretical exercise I will assign are actually well-known results; in other cases you may be able to find the answer in the literature. This is certainly the case for the current My position on this issue is that, basically, if you look up the answer somewhere it's your problem. After all, you can buy answer keys to most textbooks. The fact is, you will not have access to such, ehm, supporting material when you take your generals, or, in a more