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- W5053695 abstract "AbstractThis work analyses the state of the art in the field of Evolutionary Robotics and marks the path we select in the design of evolutionary strategies. The aim of this text is to describe the lines that we are going to follow in the foreseeable future. Our goal is to create through evolution the neural network that couples with a complex humanoid robot body. For us the problems of a non-structured environment and of Evolutionary Robotics need a sub-symbolic conexionist approach based in Nouvelle AI that can cope with the coupling among sensorimotor, neural and environment parts. We also describe the tools we choose to accomplish this task.KeywordsEvolutionary RoboticsSpiking Neural NetworksArtificial Lifesub-symbolicsmall-world topologiesCUDA" @default.
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- W5053695 date "2011-01-01" @default.
- W5053695 modified "2023-09-25" @default.
- W5053695 title "Topos 2: Spiking Neural Networks for Bipedal Walking in Humanoid Robots" @default.
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- W5053695 doi "https://doi.org/10.1007/978-3-642-21222-2_58" @default.
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