This paper considers a time-varying game with @math players. Every time slot, players observe their own random events and then take a control action. The events and control actions affect the individual utilities earned by each player. The goal is to maximize a concave function of time average utilities subject to equilibrium constraints. Specifically, participating players are provided access to a common source of randomness from which they can optimally correlate their decisions. The equilibrium constraints incentivize participation by ensuring that players cannot earn more utility if they choose not to participate. This form of equilibrium is similar to the notions of Nash equilibrium and correlated equilibrium, but is simpler to attain. A Lyapunov method is developed that solves the problem in an online fashion by selecting actions based on a set of time-varying weights. The algorithm does not require knowledge of the event probabilities and has polynomial convergence time. A similar method can be used to compute a standard correlated equilibrium, albeit with increased complexity.
A Course in Game Theory presents the main ideas of game theory at a level suitable for graduate students and advanced undergraduates, emphasizing the theory's foundations and interpretations of its basic concepts. The authors provide precise definitions and full proofs of results, sacrificing generalities and limiting the scope of the material in order to do so. The text is organized in four parts: strategic games, extensive games with perfect information, extensive games with imperfect information, and coalitional games. It includes over 100 exercises. Players choose an action before learning an outcome chosen according to an unknown and history-dependent stochastic rule. Procedures that categorize outcomes, and use a randomized variation on fictitious play within each category are studied. These procedures are â€œconditionally consistent:â€ they yield almost as high a time-average payoff as if the player knew the conditional distributions of actions given categories. Moreover, given any alternative procedure, there is a conditionally consistent procedure whose performance is no more than epsilon worse regardless of the discount factor. We also discuss cycles, and argue that the time-average of play should resemble a correlated equilibrium.   Abstract Suppose two players repeatedly meet each other to play a game where 1. each uses a learning rule with the property that it is a calibrated forecast of the other's plays, and 2. each plays a myopic best response to this forecast distribution. Then, the limit points of the sequence of plays are correlated equilibria. In fact, for each correlated equilibrium there is some calibrated learning rule that the players can use which results in their playing this correlated equilibrium in the limit. Thus, the statistical concept of a calibration is strongly related to the game theoretic concept of correlated equilibrium. Journal of Economic Literature Classification Numbers: C72,D83,C44. If it is common knowledge that the players in a game are Bayesian utility maximizers who treat uncertainty about other players' actions like any other uncertainty, then the outcome is necessarily a correlated equilibrium. Random strategies appear as an expression of each player's uncertainty about what the others will do, not as the result of willful randomization. Use is made of the common prior assumption, according to which differences in probability assessments by different individuals are due to the different information that they have (where "information" may be interpreted broadly, to include experience, upbringing, and genetic makeup). Copyright 1987 by The Econometric Society. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of th (This abstract was borrowed from another version of this item.) In this paper we propose a new class of games, the “strategically zero-sum games,” which are characterized by a special payoff structure. We show that for a large body of correlation schemes which includes the correlated strategies “a la Aumann”, strategically zero-sum games are exactly these games for which no completely mixed Nash equilibrium can be improved upon. We propose a simple adaptive procedure for playing a game. In this procedure, players depart from their current play with probabilities that are proportional to measures of regret for not having used other strategies (these measures are updated every period). It is shown that our adaptive procedure guaranties that with probability one, the sample distributions of play converge to the set of correlated equilibria of the game. To compute these regret measures, a player needs to know his payoff function and the history of play. We also offer a variation where every player knows only his own realized payoff history (but not his payoff function).