This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The decision process of individuals is described by an Evolutionary Algorithm. We find that the contribution level converges towards the Nash...

This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The decision process of individuals is described by an Evolutionary Algorithm. We analyze the learning process of purely and impurely altruistic...

This paper examines the learning dynamics of boundedly rational agents, who are asked to voluntarily contribute to a discrete public good. In an incomplete information setting, we discuss contribution games and subscription games, the latter including a money-back guarantee in case of provision...

This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The decision process of individuals is described by an Evolutionary Algorithm. We analyze the learning process of purely and impurely altruistic...

This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The dynamic game is described by an Evolutionary Algorithm, which is shown to extend the applicability of ordinary replicator dynamics of...

This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The decision process of individuals is described by an Evolutionary Algorithm. We analyze the learning process of purely and impurely altruistic...

The literature on multi-agent models up until recently has been mainly concerned with the price dynamics in a setting where agents are allowed to switch between a finite number of strategies.In reality, however, we would expect a high degree of heterogeneity, such that few belief types will...

This paper develops the notion of a Large Type Limit (LTL) describing the average behavior of adaptive evolutionary systems with many trader types. It is shown that generic and persistent features of adaptive evolutionary systems with many trader types are well described by the large type limit....

This work aims at connecting developments in the theory of agency and implicit contracts with research on bounded rationality and agent based computational models. These are two related areas as implicit contracts are justified on the basis of bounded rationality, which additionally is one of...