The theory of learning in games explores how, which, and what kind of equilibria might arise as a consequence of a long-run nonequilibrium process of learning, adaptation, and/or imitation. If agents’ strategies are completely observed at the end of each round (and agents are randomly matched...

We study the evolution of R&D networks in a Cournot model where firms may lower marginal costs due to bilateral R&D collaborations. Stochastically stable R&D networks exhibit the dominant group architecture, and, contrary to the existing literature, generically unique predictions about the size...

This paper considers marriage problems, roommate problems with nonempty core, and college admissions problems with responsive preferences. All stochastically stable matchings are shown to be contained in the set of matchings which are most robust to one-shot deviation.

We consider models of stochastic evolution in two-strategy games in which agents employ imitative decision rules. We introduce committed agents: for each strategy, we suppose that there is at least one agent who plays that strategy without fail. We show that unlike the standard imitative model,...

A recent literature in evolutionary game theory is devoted to the question of robust equilibrium selection under noisy best-response dynamics. In this paper we present a complete picture of equilibrium selection for asymmetric binary choice coordination games in the small noise limit. We achieve...

The best shot game applied to networks is a discrete model of many processes of contribution to local public goods. It generally has a wide multiplicity of equilibria that we refine through stochastic stability. We show that, depending on how we define perturbations – i.e., possible mistakes...

This paper takes the idea of coalitional behavior – groups of people occasionally acting together to their mutual benefit – and incorporates it into the framework of evolutionary game theory that underpins the social learning literature. An equilibrium selection criterion is defined which we...

We show that local potential maximizer (Morris and Ui (2005) [14]), a generalization of potential maximizer, is stochastically stable in the log-linear dynamic if the payoff functions are, or the associated local potential is, supermodular. Thus an equilibrium selection result similar to those...

This paper introduces a new coordination problem for a large but finite population – The Language Game. The population is partitioned into two groups of identical agents. Each player shares a common two-action strategy set and interacts pairwise with everyone else. Both symmetric profiles are...

An individualʼs learning rule is completely uncoupled if it does not depend directly on the actions or payoffs of anyone else. We propose a variant of log linear learning that is completely uncoupled and that selects an efficient (welfare-maximizing) pure Nash equilibrium in all generic...