Co-evolutionary learning with strategic coalition for multiagents
Applied Soft Computing
Modeling multi-agent labor market based on co-evolutionary computation and game theory
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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We present a new paradigm extending the iterated prisoner's dilemma to multiple players. Our model is unique in granting players information about past interactions between all pairs of players - allowing for much more sophisticated social behaviour. We provide an overview of preliminary results and discuss the implications in terms of the evolutionary dynamics of strategies.