Evolution of Plastic Neurocontrollers for Situated Agents

In this paper we investigate a novel approach to the evolutionary development of autonomous situated agents based on the assumption that the neural mechanisms underlying ontogenetic learning are themselves developed and shaped by evolutionary process. A genetic algorithm is used to evolve neural structures that can be continuously modified during life according to the mechanisms specified in the genotype. The evolutionary process is carried out on a real mobile robot. The analysis of one of the best evolved individuals shows rapid development of stable behavior mediated by fast-changing synapses which are dynamically stable.


Editor(s):
Maes, P.
Mataric, M.
Meyer, J.-A.
Pollack, J.
Wilson, S.
Published in:
From Animals to Animats 4, Proceedings of the 4th International Conference on Simulation of Adaptive Behavior (SAB'1996), 402-410
Presented at:
4th International Conference on Simulation of Adaptive Behavior (SAB'1996), Cape Cod, Massachusetts, September 9-13
Year:
1996
Publisher:
MA: MIT Press
Keywords:
Note:
P. Maes, M. Mataric, J-A. Meyer, J. Pollack, and S. Wilson (eds.)
Laboratories:




 Record created 2006-01-12, last modified 2018-11-14

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