The purpose of this paper is to present a method of combining neural networks and genetic algorithms to create an efficient control system for a simulated autonomous robot in a 3D environment. The experiments concern ...
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ISBN:
(纸本)9780889865952
The purpose of this paper is to present a method of combining neural networks and genetic algorithms to create an efficient control system for a simulated autonomous robot in a 3D environment. The experiments concern the emergence of behaviours like obstacle avoidance, tar-et hitting and shortest path finding using a simple yet robust architecture. The evolutionary process takes place inside a dedicated, flexible framework that allows further development and testing.
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