This survey covers models of how agents update behaviors and beliefs using information
conveyed through social connections. We begin with sequential social learning models, in …

We consider the problem of training a machine learning model over a network of nodes in a
fully decentralized framework. The nodes take a Bayesian-like approach via the introduction …

As economists endeavor to build better models of human behavior, they cannot ignore that
humans are fundamentally a social species with interaction patterns that shape their …

This chapter develops a unified framework for the study of how network interactions can
function as a mechanism for propagation and amplification of microeconomic shocks. The …

We consider the problem of distributed learning, where a network of agents collectively aim
to agree on a hypothesis that best explains a set of distributed observations of conditionally …

This paper considers a problem of distributed hypothesis testing over a network. Individual
nodes in a network receive noisy local (private) observations whose distribution is …

We overview some results on distributed learning with focus on a family of recently proposed
algorithms known as non-Bayesian social learning. We consider different approaches to the …

We study the asymptotic learning rates of belief vectors in a distributed hypothesis testing
problem under linear and log-linear combination rules. We show that under both …

We consider a group of strategic agents who must each repeatedly take one of two possible
actions. They learn which of the two actions is preferable from initial private signals and by …

This paper addresses the problem of distributed detection in multi-agent networks. Agents
receive private signals about an unknown state of the world. The underlying state is globally …