Evolving agent socienties that avoid social dilemmas

The social sciences literature abound in problems of providing and maintaining a public good in a society composed of self-interested individuals [8]. Public goods are social benefits that can be accessed by individuals irrespective of their personal contributions. In our previous work we have demonstrated the use of genetic algorithms (GAs) for generating an optimized agent society that can circumvent a particularly problematic social dilemma. In that approach, each chromosome represented the entire agent society and the GA found the best co-adapted society. Though encouraging, this result is less exciting than the possibility of evolving a set of co-adapted chromosomes where each chromosome represent an agent, and hence the population represents the society. In this paper, we describe our approach to using such an adaptive systems approach to using GAs for evolving agent societies. We present experimental results from several domains including the classic problem of the Tragedy of the Commons [17].

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