This paper provides a model of social learning where the order in which actions are taken is determined by an m-dimensional integer lattice rather than along a line as in the herding model. The observation structure is determined by a random network. Every agent links to each of his preceding...

This paper analyzes a sequential social learning game with a general utility function, state and action space. We show that asymptotic learning holds for every utility function if and only if signals are totally unbounded, i.e., the support of the private posterior probability of every event...