The paper analyzes a dynamic model of rational strategic learning in a network. It complements existing literature by … network. We show that the delay in information transmission caused by incomplete network structures may induce players to … increase own experimentation efforts. As a consequence a complete network can fail to be optimal even if there are no costs for …

This paper studies fictitious play in networks of noncooperative two-person games. We show that continuous … convergence is 1/T, regardless of the size of the network. In contrast, arbitrary n-person zero-sum games with bilinear payoff … functions do not possess the continuous-time fictitious-play property. As extensions, we consider networks in which each …

Agents in a network want to learn the true state of the world from their own signals and their neighbors' reports …. Agents know only their local networks, consisting of their neighbors and the links among them. Every agent is Bayesian with … the (possibly misspecified) prior belief that her local network is the entire network. We present a tractable learning …

Individuals have a strong tendency to coordinate with all their neighbors on social and economics networks … multiplex network who deal with coordination issues using social learning and payoff-driven dynamics. Agents form their …

' actions in terms of network paths and use this formula to characterize the set of networks where naive agents eventually learn …We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents … correctly. This characterization implies that, on all networks where later agents observe more than one neighbor, there exist …

We introduce a model of strategic experimentation on social networks where forwardlooking agents learn from their own … own experimentation, so total information decreases with network density; we determine density thresholds below which … agents asymptotically learn the state. In contrast, agent welfare is single-peaked in network density, and achieves a second …

social network - can influence our choices. These choices in turn influence the generation of new information and shape … future choices. These considerations motivate a rich research programme on how social networks shape individual and …

The novelty of our model is to combine models of collective action on networks with models of social learning. Agents … are connected according to an undirected graph, the social network, and have the choice between two actions: either to … network. (2) Average inclination governs collective adoption behavior. (3) Initial inclinations determine the critical mass of …

Agents in a network want to learn the true state of the world from their own signals and their neighbors' reports …. Agents know only their local networks, consisting of their neighbors and the links among them. Every agent is Bayesian with … the (possibly misspecified) prior belief that her local network is the entire network. We present a tractable learning …