Learning and selfconfirming equilibria in network games

• 成果类型: Article
• 署名作者: Battigalli, Pierpaolo; Panebianco, Fabrizio; Pin, Paolo
• 署名单位: Bocconi University; Catholic University of the Sacred Heart; University of Siena; Bocconi University; Bocconi University; Catholic University of the Sacred Heart
• 刊物名称: JOURNAL OF ECONOMIC THEORY
• ISSN/ISSBN: 0022-0531
• DOI: 10.1016/j.jet.2023.105700
• 发表日期: 2023
• 关键词: Learning; Selfconfirming equilibrium; Network games; Observability by active players; Shallow conjectures

摘要

Consider a set of agents who play a network game repeatedly. Agents may not know the network. They may even be unaware that they are interacting with other agents in a network. Possibly, they just understand that their optimal action depends on an unknown state that is, actually, an aggregate of the actions of their neighbors. In each period, every agent chooses an action that maximizes her instantaneous subjective expected payoff and then updates her beliefs according to what she observes. In particular, we assume that each agent only observes her realized payoff. A steady state of the resulting dynamic is a selfconfirming equilibrium given the assumed feedback. We identify conditions on the network externalities, agents' beliefs, and learning dynamics that make agents more or less active (or even inactive) in steady state compared to Nash equilibrium.& COPY; 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons .org /licenses /by -nc -nd /4 .0/).