Under the assumption that individuals know the conditional distributions of signals given the payoff-relevant parameters, existing results conclude that as individuals observe infinitely many signals, their beliefs about the parameters will eventually merge. We first show that these results are...

We study perfect Bayesian equilibria of a sequential social learning model in which agents in a network learn about an underlying state by observing neighbors' choices. In contrast with prior work, we do not assume that the agents' sets of neighbors are mutually independent. We introduce a new...

In this paper, I provide a characterization of a \textit{set} of probability measures with which a prior ``weakly merges.'' In this regard, I introduce the concept of ``conditioning rules'' that represent the \textit{regularities% } of probability measures and define the ``eventual generation''...

We provide an overview of recent research on belief and opinion dynamics in social networks. We discuss both Bayesian and non-Bayesian models of social learning and focus on the implications of the form of learning (e.g., Bayesian vs. non-Bayesian), the sources of information (e.g., observation...

This paper studies the effect of trade opportunities on a seller's incentive to acquire information through experimentation. I characterize the unique equilibrium outcome and discuss the effects of variations in the information structure on the probability of trade. The main result is that more...

In this paper, we investigate the condition under which players of an adaptive learning model, including the one of stochastic fictitious play learning, learn to follow a logit quantal response equilibrium corresponding to a strict Nash equilibrium, the one which approaches the Nash equilibrium...

We conducted controlled laboratory experiments to investigate how humans adapt the decision rule (DR) they use in repeated strategic interactions in light of new information becoming available. We do so by providing -- along different paths -- more and more information over time, so as to...

I present a model of observational learning with payoff interdependence. Agents, ordered in a sequence, receive private signals about an uncertain state of the world and sample previous actions. Unlike in standard models of observational learning, an agent's payoff depends both on the state and...

Observational learning is typically examined when agents have precise information about their position in the sequence of play. We present a model in which agents are uncertain about their positions. Agents sample the decisions of past individuals and receive a private signal about the state of...

This paper studies the interaction between coordination and social learning in a dynamic regime change game. Social learning provides public information, to which players overreact due to the coordination motive. Coordination affects the aggregation of private signals through players' optimal...