In many experiments, the Nash equilibrium concept seems not to predict well. One reason may be that players have non-selfish preferences over outcomes. As a consequence, even when they are told what the material payoffs of the game are, mutual knowledge of preferences may not be satisfied. We...

Algorithms for equilibrium computation generally make no attempt to ensure that the computed strategies are understandable by humans. For instance the strategies for the strongest poker agents are represented as massive binary files. In many situations, we would like to compute strategies that...

We provide a framework for studying two-sided matching markets with incomplete information. The framework accommodates two-sided incomplete information as well as heterogeneous information among the agents. We propose a notion called stability for a market state, which, based upon agents'...

We study a two-sided job market matching setting with transferable utilities and incomplete information on both sides. We propose a definition of stable matching with two-sided incomplete information. Assume that the workers and firms' premuneration values in a match are strictly monotonic and...

A standing question in the theory of matching markets is how to define stability under incomplete information. This paper proposes an epistemic approach. Agents negotiate through offers, and offers are interpreted according to the highest possible degree of rationality that can be ascribed to...

A principal delegates a sequential search in finite horizon to an agent, who bears the search cost and controls when to terminate the search. Upon termination, the search payoff is split between the principal and agent. However, only the principal can evaluate each search outcome, whose value is...