Evolution and analysis of dynamical neural networks for agents integrating vision, locomotion, and short-term memory

摘要

The use of evolutionary approaches to create dynamical "nervous systems" for autonomous agents is becoming increasingly widespread. In previous work, we have successfully applied this approach to chemotaxis, walking, learning, and such minimally cognitive behavior as visually-guided orientation, object discrimination and pointing. In this paper, we extend this approach to the integration of visually-guided orientation and walking and to an object orientation task that requires short-term memory. In addition, we examine the neural dynamics underlying the operation of some of these evolved agents.