This paper studies the adaptive learning dynamics over multiple locations. Our focus is to show that, to observe the average performance of other locations is necessary or efficient. Through the analysis of information structure, the result about convergence and stochastic stability can be...

This paper studies the aspiration-based learning dynamics in symmetric normal-form games played at multiple locations. In particular, the aspiration level in one location is linked to the average performances of players in observable locations. With a decentralized information structure, the...

This paper considers a finite population of agents located within an arbitrary fixed network. Every agent plays a coordination game with his neighbors. If one neighbor's payoff from a specific interaction exceeds his average payoff per interaction, the neighbor is perceived as better performing....

This paper considers one-way flow network formation games in which transmission through a series of agents is subject to decay. We analyze the myopic best-response dynamics of network formation games, occasionally perturbed by state-dependent random noises. Specifically, if an agent is isolated...

This paper explores the medium-run behaviour of bounded rational players in repeatedly played games when they occasionally experiment or make mistakes. The formal analysis introduces a hierarchical structure of limit sets to characterize the most possible medium-run behaviour over gradually...

This paper studies the aspiration-based learning dynamics in symmetric normal-form games played at multiple locations. In particular, the aspiration level in one location is linked to the average performances of players in observable locations. With a decentralized information structure, the...