Decision theory can be used to test the logic of decision making---one may ask whether a given set of decisions can be justified by a decision-theoretic model. Indeed, in principal-agent settings, such justifications may be required---a manager of an investment fund may be asked what beliefs she...

This paper examines circumstances under which subjectivity enhances the effectiveness of inductive reasoning. We consider agents facing a data generating process who are characterized by inference rules that may be purely objective (or data-based) or may incorporate subjective considerations....

We examine an evolutionary model with "local interactions," so that some agents may be more likely to interact than others. We show that equilibrium strategy choices with given local interactions correspond to correlated equilibria of the underlying game, suggesting an new interpretation for...

This paper examines circumstances under which subjectivity enhances the effectiveness of inductive reasoning. We consider a game in which Fate chooses a data generating process and agents are characterized by inference rules that may be purely objective (or data-based) or may incorporate...

We examine a repeated interaction between an agent, who undertakes experiments, and a principal who provides the requisite funding for these experiments. The repeated interaction gives rise to a dynamic agency cost—the more lucrative is the agent’s stream of future rents following a failure,...

We examine a repeated interaction between an agent, who undertakes experiments, and a principal who provides the requisite funding for these experiments. The repeated interaction gives rise to a dynamic agency cost — the more lucrative is the agent’s stream of future rents following a...

We study maximum-likelihood estimation and updating, subject to computational, cognitive, or behavioral constraints. We jointly characterize constrained estimates and updating within a framework reminiscent of a machine learning algorithm. Without frictions, the framework simplifies to standard...

We examine a repeated interaction between an agent, who undertakes experiments, and a principal who provides the requisite funding for these experiments. The agent's actions are hidden, and the principal, who makes the offers, cannot commit to future actions. We identify the unique Markovian...

We examine an evolutionary model in which the primary source of "noise" that moves the model between equilibria is not random, arbitrarily improbable mutations but mistakes in learning. We find conditions under which the payoff-dominant equilibrium in a 2x2 game is selected by the model as well...

We formulate a dynamic learning-and-adjustment model of a market in which sellers choose signals that potentitally reveal their types. If the dynamic process selects a unique limiting outcome, then that outcome must be an undefeated equilibrium; though to be undefeated does not suffice to be the...