If we express our knowledge in sentences, we will find that these sentences to some extent are linked by logical rules. We ask whether the structure logic imposes on our knowledge restricts what we forget and what we remember. The model is a two period S5-style modal logic. In this logic we...

This paper proposes a procedurally rational solution concept for two-person extensive-form games with complete information. The solution concept is based on the observation that the ex-post justifiability of choices is often a primary concern for decision-makers, especially in organizations. The...

In a self-confirming equilibrium, each player correctly forecasts the actions that opponents will take along the equilibrium path, but may be mistaken about the way that opponents would respond to deviations. This models a steady state of a learning process in which players observe actions...

This paper surveys implementation theory when players have incomplete or asymmetric information, especially in economic environments. After the basic problem is introduced, the theory of implementation is summarized. Some coalitional considerations for implementation problems are discussed. For...

Intuitively, a patient trader should be able to make his trading partners compete to reveal whatever information is relevant to their transactions with him. This possibility is examined in the context of a model resembling that of Gale (1986). The main result is that, under assumptions having to...

This paper surveys cooperative game theory when players have incomplete or asymmetric information, especially when the TU and NTU games are derived from economic models. First some results relating balanced games and markets are summarized, including theorems guaranteeing that the core is...

We report on experiments that tested the predictions of competing theories of learning in games. Experimental subjects played a version of the three-person matching-pennies game. The unique mixed-strategy Nash equilibrium of this game is locally unstable under naive Bayesian learning....