Evolutionary Optimization of Societies in Simulated Multi-Agent Systems

In this paper we show how to use evolutionary optimization in multi-agent systems with simple, non deliberative agents to evolve successful interaction in societies, mostly for task allocation based problems. The presented generic optimization scheme – which is implemented based on the multi-agent simulation tool SeSAm – was used to model prehistoric ant species. The idea was to show how solitary individuals evolve to societies. Results from these experiments are given. Finally future plans are discussed and evaluated.

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