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This paper presents a self-adaptive algorithm that hybridises evolutionary and multiagent concepts. Each evolutionary individual is implemented as a simple agent capable of reproduction and predation. The transitions between these two states depend on the agent's local environment. Thus, no explicit global process is defined to select neither the mates nor the preys. The convergence of the algorithm emerges from the behaviour of the agents. This brings interesting properties, such as populationdoi:10.1145/1276958.1277198 dblp:conf/gecco/HippolyteBCEC07 fatcat:dotsoeaynreodk3ocbu2tryenq