convergence is 1/T, regardless of the size of the network. In contrast, arbitrary n-person zero-sum games with bilinear payoff … requires a condition on bilateral payoffs or, alternatively, that the network is acyclic. Our results hold also for the …

Agents in a network want to learn the true state of the world from their own signals and their neighbors' reports … the (possibly misspecified) prior belief that her local network is the entire network. We present a tractable learning … reports in her local network. Despite their limited network knowledge, agents learn correctly when the network is a social …

We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents …' actions in terms of network paths and use this formula to characterize the set of networks where naive agents eventually learn … expected welfare losses, across network structures. The probability of mislearning increases when link densities are higher and …

multiplex network who deal with coordination issues using social learning and payoff-driven dynamics. Agents form their …

been covered entirely by previous diffusion models: the network character of knowledge, compatibility of new knowledge with … already existing knowledge, and the fact that transmission of knowledge requires some form of attention. We employ a network …-of-networks approach, where agents are located within an innovation network and each agent itself contains another network composed of …