We examine collaboration in a one-arm bandit problem in which the players' actions affect the distribution over future payoffs. The players need to exert costly effort both to enhance the value of a risky technology and to learn about its current state. Both product value and learning are public...

We examine collaboration in a one-arm bandit problem in which the players' actions affect the distribution over future payoffs. The players need to exert costly effort both to enhance the value of a risky technology and to learn about its current state. Both product value and learning are public...

We incorporate the process of policy diffusion (i.e. the uncoordinated dissemination of policies among countries) into a probabilistic two-country-model of strategic environmental policy. Contrary to the usual setting with simultaneous decision making we consider the impact of sequential...

We incorporate the process of policy diffusion (i.e. the uncoordinated dissemination of policies among countries) into a probabilistic two-country-model of strategic environmental policy. Contrary to the usual setting with simultaneous decision making we consider the impact of sequential...

The market of private health insurance is characterised by high level of consumer inertia. Low consumer activity is probably linked to product complexity, abundance of choice options and low consumer understanding. These factors may overwhelm consumers and reduce willingness to engage with the...

In minority games, players in a group must decide at each round which of two available options to choose, knowing that only subjects who picked the minority option obtain a positive reward. Previous experiments on the minority and similar congestion games have shown that players interacting...

In this paper I define an evolutionary stability criterion for learning rules. Using Monte Carlo simulations, I then apply this criterion to a class of learning rules that can be represented by Camerer and Ho's (1999) model of learning. This class contains perturbed versions of reinforcement and...

This paper formalizes the idea that more hedging instruments may destabilize markets when traders are heterogeneous and adapt their behavior according to experience based reinforcement learning. We investigate three different economic settings, a simple mean-variance asset pricing model, a...

With the advent of big data, unique opportunities arise for data collection and analysis and thus for personalized pricing. We simulate a self-learning algorithm setting personalized prices based on additional information about consumer sensitivities in order to analyze market outcomes for...