In a population with a local interaction structure, where individuals interact with their neighbors and learning is by way of imitating a successful neighbor, cooperation is shown to be a stable strategy that cannot easily be eliminated from the population.

This paper studies a population of agents, each of whom can be either an Altruist or an Egoist. Altruists confer benefits on others at a cost to themselves. Altruism is thus a strictly dominated strategy and cannot survive if agents are rational best-responders. We assume that agents choose...

The paper provides an explanation for altruistic behavior based on the matching and learning technology in the population. In a infinite structured population, in which individuals meet and interact with their neighbors, individuals learn by imitating their more successful neighbors. We ask...

Lecture on the first SFB/TR 15 meeting, Gummersbach, July, 18 - 20, 2004We model the formation of a herd as a game between a predator and a prey population. The predator receives some information about the composition of the herd when he chases it, but receives no information when he chases a...

A model of a population with a Local Interaction structure is presented. Individuals interact with others in a given Interaction neighborhood to obtain their payoff. Individuals either imitate or else they die and are replaced by one of their neighbors in another neighborhood- the Propagation...

This paper shows that Nash equilibria of a local-interaction game are equivalent to correlated equilibria of the underlying game.

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...