Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects

Abstract

This paper describes how the SGOCE paradigm has been used to evolve developmental programs capable of generating recurrent neural networks that control the behavior of simulated insects. This paradigm is characterized by an encoding scheme, by an evolutionary algorithm, by syntactic constraints, and by an incremental strategy that are described in turn. The… (More)
DOI: 10.1109/72.712153

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@article{Kodjabachian1998EvolutionAD, title={Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects}, author={J{\'e}r{\^o}me Kodjabachian and Jean-Arcady Meyer}, journal={IEEE transactions on neural networks}, year={1998}, volume={9 5}, pages={796-812} }