2018/12/31 by Pierpaolo Battigalli, Battigalli, Pierpaolo, Fabrizio Panebianco +3 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · Social Sciences · #Computer Science and Game Theory (cs.GT) #Economic theories and models #Experimental Behavioral Economics Studies #FOS: Computer and information sciences #FOS: Economics and business #Game Theory and Applications #Theoretical Economics (econ.TH)
paper · pdf · doi:10.48550/arxiv.1812.11775
openalex publication_date 2018/12/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 payoffs depend on an unknown state that is, actually, an aggregate of the actions of their neighbors. Each time, 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 characterize the structure of the set of selfconfirming equilibria in the given class of network games, we relate selfconfirming and Nash equilibria, and we analyze simple conjectural best-reply paths whose limit points are selfconfirming equilibria.