LEARNING, MUTATION, AND LONG-RUN EQUILIBRIA IN GAMES

• 成果类型: Article
• 署名作者: KANDORI, M; MAILATH, GJ; ROB, R
• 署名单位: Princeton University; University of Pennsylvania
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.2307/2951777
• 发表日期: 1993
• 页码: 29-56
• 关键词: STABLE STRATEGIES; DYNAMICS; COOPERATION; EVOLUTION

摘要

We analyze an evolutionary model with a finite number of players and with noise or mutations. The expansion and contraction of strategies is linked-as usual-to their current relative success, but mutations-which perturb the system away from its deterministic evolution-are present as well. Mutations can occur in every period, so the focus is on the implications of ongoing mutations, not a one-shot mutation. The effect of these mutations is to drastically reduce the set of equilibria to what we term ''long-run equilibria.'' For 2 x 2 symmetric games with two symmetric strict Nash equilibria the equilibrium selected satisfies (for large populations) Harsanyi and Selten's (1988) criterion of risk-dominance. In particular, if both strategies have equal security levels, the Pareto dominant Nash equilibrium is selected, even though there is another strict Nash equilibrium.