Adaptive individuals in evolving populations: models and algorithms
Adaptive individuals in evolving populations: models and algorithms
Evolutionary neurocontrollers for autonomous mobile robots
Neural Networks - Special issue on neural control and robotics: biology and technology
Autonomous Robots
Is there another new factor in evolution?
Evolutionary Computation
Evolving mobile robots in simulated and real environments
Artificial Life
Evolutionary Robots with Fast Adaptive Behaviour in New Environments
ICES '00 Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware
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This paper is concerned with artificial evolution of neurocontrollers with adaptive synapses for autonomous mobile robots. The method consists of encoding on the genotype a set of local modification rules that synapses obey while the robot freely moves in the environment [2]. The synaptic weights are not encoded on the genotype. In the experiments presented here, a "behavior-based fitness" function gives reproductive advantage to robots that can solve a sequential task. The results show that evolutionary adaptive controllers solve the task much faster and better than evolutionary standard (non-adaptive) controllers, that the method scales up well to large architectures whereas standard controllers do not, and that evolved adaptive controllers are not trivial and cannot be reduced to a fixed-weight network.