This paper briefly reviews synthetic approaches to neurobiology and presents results of two experiments on the use of evolutionary algorithms for the design of neural controllers for locomotion. The first experiment consists in using the evolutionary algorithm for instantiating low level parameters of a connectionist simulation of the lamprey's locomotor circuitry. The second experiment develops potential neural circuits for the swimming and trotting of the salamander; an animal whose locomotor circuitry has currently not been deconded. In both cases, biologically plausible control circuits are developed which produce a neural activity with many simularities to that measured in the real animals.
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