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Adapting Control Strategies for Situated Autonomous

This paper studies how to balance evolutionary design and human expertise in order to best design situated autonomous agents which can learn speciic tasks. A genetic algorithm designs control circuits to learn simple behaviors, and given control strategies for simple behaviors, the genetic algorithm designs a combinational circuit that switches between these simple behaviors to perform a navigation task.