ON THE EMERGENCE OF SOCIAL CONVENTIONS - MODELING, ANALYSIS, AND SIMULATIONS

We define the notion of social conventions in a standard game-theoreti c framework, and identify various criteria of consistency of such conv entions. with the principle of individual rationality. We then investi gate the emergence of such conventions in a stochastic setting; we do so within a stylized framework currently popular in economic circles, namely that of stochastic games. This framework comes in several forms ; in our setting agents interact with each other through a random proc ess, and accumulate information about the system. As they do so, they continually reevaluate their current choice of strategy in light of th e accumulated information. We introduce a simple and natural strategy- selection rule, called highest cumulative reward (HCR). We show a clas s of games in which HCR guarantees eventual convergence to a rationall y acceptable social convention. Most importantly, we investigate the e fficiency with which such social conventions are achieved. We give an analytic lower bound on this rate, and then present results about how HCR works out in practice. Specifically, we pick one of the most basic games, namely a basic coordination game (as defined by Lewis), and th rough extensive computer simulations determine not only the effect of applying HCR, but also the subtle effects of various system parameters , such as the amount of memory and the frequency of update performed b y all agents. (C) 1997 Elsevier Science B.V.