Fitness functions in evolutionary robotics: A survey and analysis
Robotics and Autonomous Systems
An algorithm for distributed on-line, on-board evolutionary robotics
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Natural Computing: an international journal
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Research in the field of evolutionary robotics has begun to investigate the evolution of learning controllers for autonomous robots. Research in this area has achieved promising results, but research to date has focussed on the evolution of neural networks incorporating synaptic plasticity. There has been little investigation of possible alternatives, although the importance of exploring such alternatives is recognised. This paper describes a first step towards addressing this issue. Using networks with fixed synaptic weights and 'leaky integrator' neurons, we evolve robot controllers capable of learning and thus exploiting regularities occurring within their environment.