Many interactive environments can be represented as games, but they are so large and complex that individual players are in the dark about others' actions and the payoff structure.  This paper analyzes learning behavior in such 'black box' environments, where players' only source of information...

We conduct a field experiment to investigate employers' trust in workers.  A sample of real entrepreneurs and workers from urban Ghana are respectively assigned to the roles of employers and employees.  Employers have the option to hire (trust) an employee, who can in turn choose whether to...

In this paper we address the question as to why fund managers may trade on short-term information in a financial market that offers more profitable trading on long-term information. We consider a setting in which a fund manager`s ability is unknown and an investor uses performance observations...

We study evolutionary dynamics in assignment games where many agents interact anonymously at virtually no cost.  The process is decentralized, very little information is available and trade takes place at many different prices simultaneously.  We propose a completely uncoupled learning process...

In this paper we investigate how cognitive ability and character skills influence behavior, success and the evolution of play towards Nash equilibrium in repeated strategic interactions.  We study behavior in a p-beauty contest experiment and find striking differences according to cognitive...

In an environment where voters face an inference problem on the competence level of policy makers, this paper shows how subjecting these policy makers to reelection can reduce the degree of policy experimentation to the benefit of the status quo.  This may be a reason why some notable policy...

People believe that, even in very large samples, proportions of binary signals might depart significantly from the population mean.  We model this "non-belief in the Law of Large Numbers" by assuming that a person believes that proportions in any given sample might be determined by a rate...

This paper studies learning in monotone Bayesian games with one-dimensional types and finitely many actions. Players switch between actions at a set of thresholds.  A learning algorithm under which players adjust their strategies in the direction of better ones using payoffs received at...

This paper presents a neural network model developed to simulate the endogenous emergence of bounded-rational behavior in normal-form games. There exists an algorithm which, if learnt by a neural network, would enable it to perfectly select Nash equilibria in never before seen games. However,...

This paper examines experimental evidence relating to herd behaviour in situations when subjects can learn from each other, and can delay their decision. Subjects acted rationally, gaining from observational learning, despite penalties for delay. Cascades were ubiquitous and reverse-cascades...