Since the early beginnings of Evolutionary Computation, Finite State Machines (FSMs) have been applied to model organisms. We present a new approach to evolve such artificial organisms. The FSMs are subject to a difficult navigation and searching task in heterogeneous environments. We give a definition of FSM-species and investigate their formation. The results show that species are formed as the organisms agree on a common 'genetic broadcast language' and take advantage of the fruitful effects of recombination. As observed in natural ecosystes, higher abiotic diversity leads to higher biotic diversity.
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