اولویت تکامل، سرعت دینامیک و تغییر سریع اجتماعی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|16953||2001||43 صفحه PDF||سفارش دهید||16430 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Review of Economic Dynamics, Volume 4, Issue 3, July 2001, Pages 637–679
We present a dynamic analysis of the evolution of preferences in a strategic environment. In our model, each player's behavior depends on both the game's payoffs and his idiosyncratic biases, but only the game's payoffs determine his evolutionary success. Dynamics run at two speeds at once; while natural selection slowly reshapes the distribution of preferences, players quickly learn to behave as their preferences dictate. We establish the existence and uniqueness of the paired trajectories of society's preferences and behavior. While aggregate behavior adjusts smoothly in equilibration games, in coordination games aggregate behavior can jump discretely in an instant of evolutionary time. Journal of Economic Literature Classification Numbers: C72, C73.
The origins of evolutionary game theory lie in biological models of natural selection. The players in these models are animals genetically programmed to play a certain strategy; evolution is driven by differences in their reproductive success. Economists have adapted models from evolutionary game theory to study the dynamics of human behavior.
نتیجه گیری انگلیسی
We have analyzed an explicitly dynamic model of preference evolution, establishing the existence and uniqueness of the evolutionary solution paths. To keep the analysis as simple as possible,we have restricted attention to games with two strategies and to preferences which can be represented in terms of biases. There are many applications of large population games in which players face binary choices,25 and biases seem a natural form of variation in individual preferences. Nevertheless,understanding the dynamics of preference evolution in more general strategic settings and under broader classes of preferences is an important topic for future research.