Resolving social dilemmas using genetic algorithms

A challenging problem for designers of agent so-cieties is the problem of providing for public goods (Hardin 1968). Public goods are social benefits that can be accessed by individuals ir-respective of their personal contributions. The dilemma for an individual agent is whether to be a contributor or to be an exploiter (enjoy bene-fits without contributing proportionately). It has been shown that selfish actions on the part of agents in a society can lead to ineffective social systems. In this paper, we evolve agent societies which are able to "solve " the dilemma. In one set of experiments, a genetic algorithm (GA) based approach is used to evolve agent societies that are faced with the Bracss ’ paradox (Irvine 1993). In another scenario, agent groups adapt to effec-tively utilize a pair of resources. Encouraged by this initial explorations, we plan to investigate another variation of the GA that uses less global information than the current approach