Аннотация:This paper analyses the strengths and weaknesses of self-organizing approaches, such as evolutionary robotics, and direct design approaches, such as behavior-based controllers, for the production of autonomous robots' controllers, and shows how the two approaches can be usefully combined.In particular, the paper proposes a method for encoding evolved neural network-based behaviors into motor schema-based controllers and then shows how these controllers can be modified and combined to produce robots capable of solving new tasks.The method has been validated in the context of a collective robotics scenario, in which a group of physically assembled simulated autonomous robots are requested to produce different forms of coordinated behaviors (e.g., coordinated motion, walled-arena exiting, and light pursuing).
