Abstract: | The aim of this project is to study and to compare biological and artificially evolved neural networks controlling the motion of an animal: the anguilliform swimming of a lamprey. The neural swimming controller of the lamprey, extensively studied and modeled by Grillner and Ekeberg, is reproduced. Evolutionary computing methods are used to develop alternative artificial controllers composed of neurons similar to those used in the biological model. This project studies the feasibility of using Genetic Algorithms to evolve neural controllers and evaluates the quality of the evolved networks by comparing them with the biological controller. Results show that artificial controllers can be obtained with other architectures than the biological one, and which, in some way, are more efficient.
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