This paper models the dynamic process through which a large society may succeed in building up its "social capital" by establishing a stable and dense pattern of interaction among its members. In the model, agents interact according to a collection of infinitely repeated Prisoner's Dilemmas...

This paper analyses the efficient management of nonpoint source pollution (NPS) under limited pollution control budget and incomplete information inherent in NPS pollution. By incorporating information acquisition into a pollution control model, it focuses on the tradeoff between data collection...

This paper analyses budget-constrained, nonpoint source (NPS) pollution control with costly information acquisition and learning. To overcome the inherent ill-posed statistical problem in NPS pollution data the sequential entropy filter is applied to the sediment load management program for...

We study learning and influence in a setting where agents communicate according to an arbitrary social network and naïvely update their beliefs by repeatedly taking weighted averages of their neighbors' opinions. A focus is on conditions under which beliefs of all agents in large societies...

We present experiments on repeated non-cooperative network formation games, based on Bala and Goyal (2000). We treat the one-way and the two-ways flow models, each for high and low link costs. The models show both multiple equilibria and coordination problems. We conduct experiments under...

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...

Dieser Beitrag gibt einen Überblick über Ansatzpunkte und Möglichkeiten zur Integration von Lernprozessen in volkswirtschaftliche Fragestellungen. Es werden alternative Methoden vorgestellt, individuelle aber auch gesellschaftliche Lernenvorgänge in ökonomischen Modellen zu erfassen.

Das Papier untersucht, wie Erwartungsbildung mit Hilfe neuronaler Netze modelliert werden kann. Die Grundlage bildet ein Cobweb-Modell, in dem Firmen Preiserwartungen auf Basis eines Feedforward-Netzes bilden. Zunächst wird anhand von Simulationen gezeigt, daß Firmen durch neuronale...

This article tries to connect two separate strands of literature concerning genetic algorithms. On the one hand, extensive research took place in mathematics and closely related sciences in order to find out more about the properties of genetic algorithms as stochastic processes. On the other...

This paper tries to connect the theory of genetic algorithm (GA) learning to evolutionary game theory. It is shown that economic learning via genetic algorithms can be described as a specific form of evolutionary game. It will be pointed out that GA learning results in a series of near Nash...