Literature DB >> 10021764

Forming neural networks through efficient and adaptive coevolution

.   

Abstract

This article demonstrates the advantages of a cooperative, coevolutionary search in difficult control problems. The symbiotic adaptive neuroevolution (SANE) system coevolves a population of neurons that cooperate to form a functioning neural network. In this process, neurons assume different but overlapping roles, resulting in a robust encoding of control behavior. SANE is shown to be more efficient and more adaptive and to maintain higher levels of diversity than the more common network-based population approaches. Further empirical studies illustrate the emergent neuron specializations and the different roles the neurons assume in the population.

Year:  1997        PMID: 10021764     DOI: 10.1162/evco.1997.5.4.373

Source DB:  PubMed          Journal:  Evol Comput        ISSN: 1063-6560            Impact factor:   3.277


  3 in total

1.  Maximizing adaptive power in neuroevolution.

Authors:  Paolo Pagliuca; Nicola Milano; Stefano Nolfi
Journal:  PLoS One       Date:  2018-07-18       Impact factor: 3.240

2.  Mapping function onto neuronal morphology.

Authors:  Klaus M Stiefel; Terrence J Sejnowski
Journal:  J Neurophysiol       Date:  2007-04-11       Impact factor: 2.714

3.  An attractor-based complexity measurement for Boolean recurrent neural networks.

Authors:  Jérémie Cabessa; Alessandro E P Villa
Journal:  PLoS One       Date:  2014-04-11       Impact factor: 3.240

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.