We study compliance dynamics generated by a large set of behavioral rules describing social interaction in a population of agents facing an enforcement authority. When the authority adjusts the auditing probability every period, cycling in cheating-auditing occurs: Intensive monitoring induces...

We study compliance dynamics generated by a large set of behavioral rules describing social interaction in a population of agents facing an enforcement authority. When the authority adjusts the auditing probability every period, cycling in cheating-auditing occurs: Intensive monitoring induces...

We study compliance dynamics generated by a large set of behavioral rules describing social interaction in a population of agents facing an enforcement authority. When the authority adjusts the auditing probability every period, cycling in cheating-auditing occurs: Intensive monitoring induces...

We study evolutionary dynamics in assignment games where many agents interact anonymously at virtually no cost.  The process is decentralized, very little information is available and trade takes place at many different prices simultaneously.  We propose a completely uncoupled learning process...

We build a search-and-matching algorithm of network dynamics with decision-making under incomplete information, seeking to understand the determinants of the observed gradual downgrading of expert opinion on complicated issues and the decreasing trust in science. Even without fake news,...

We consider an economy where trade is decentralized and agents have incomplete information with respect to the value of money. Agents' learning evolves from private experiences and we explore how the formation of prices interacts with learning. We show that multiple equilibria arise, and...

Equilibrium selection in the Nash demand game is investigated in a learning context with persistent randomness. I adopt a matching framework similar to Kandori, Mailath and Rob (1993) and assume that individuals belong to populations of different sizes. Despite the myopic behavior of...

We build a search-and-matching algorithm of network dynamics with decision-making under incomplete information, seeking to understand the determinants of the observed gradual downgrading of expert opinion on complicated issues and the decreasing trust in science. Even without fake news,...

We build a model of network dynamics with decision-making under incomplete information in order to understand the determinants of the observed gradual downgrading of expert opinion on complicated issues and the decreasing trust in science. We suggest a search and matching mechanism behind...

In consectutive rounds, each agent in a finite population chooses an action, is randomly matched, obtains a payoff and then observes the performance of another agent. An agent determines future behavior based on the information she receives from the present round. She chooses among the...