Publikation: Impact of neuron models and network structure on evolving modular robot neural network controllers
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This paper investigates the properties required to evolve Artificial Neural Networks for distributed control in modular robotics, which typically involves non-linear dynamics and complex interactions in the sensori-motor space. We investigate the relation between macro-scale properties (such as modularity and regularity) and micro-scale properties in Neural Network controllers. We show how neurons capable of multiplicative-like arithmetic operations may increase the performance of controllers in several ways whenever challenging control problems with non-linear dynamics are involved. This paper provides evidence that performance and robustness of evolved controllers can be improved by a combination of carefully chosen micro- and macro-scale neural network properties.
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CAZENILLE, Leo, Nicolas BREDECHE, Heiko HAMANN, Jürgen STRADNER, 2012. Impact of neuron models and network structure on evolving modular robot neural network controllers. GECCO '12 : 14th annual conference on Genetic and evolutionary computation. Philadelphia, Pennsylvania, 7. Juli 2012 - 11. Juli 2012. In: SOULE, Terence, ed. and others. GECCO '12 : Proceedings of the 14th annual conference on Genetic and evolutionary computation. New York, NY: ACM, 2012, pp. 89-96. ISBN 978-1-4503-1177-9. Available under: doi: 10.1145/2330163.2330177BibTex
@inproceedings{Cazenille2012Impac-59916, year={2012}, doi={10.1145/2330163.2330177}, title={Impact of neuron models and network structure on evolving modular robot neural network controllers}, isbn={978-1-4503-1177-9}, publisher={ACM}, address={New York, NY}, booktitle={GECCO '12 : Proceedings of the 14th annual conference on Genetic and evolutionary computation}, pages={89--96}, editor={Soule, Terence}, author={Cazenille, Leo and Bredeche, Nicolas and Hamann, Heiko and Stradner, Jürgen} }
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