Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolution

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

6 Citaten (Scopus)
70 Downloads (Pure)


Many real-world control and classification tasks involve a large number of features. When artificial neural networks (ANNs) are used for modeling these tasks, the network architectures tend to be large. Neuroevolution is an effective approach for optimizing ANNs; however, there are two bottlenecks that make their application challenging in case of high-dimensional networks using direct encoding. First, classic evolutionary algorithms tend not to scale well for searching large parameter spaces; second, the network evaluation over a large number of training instances is in general time-consuming. In this work, we propose an approach called the Limited Evaluation Cooperative Co-evolutionary Differential Evolution algorithm (LECCDE) to optimize high-dimensional ANNs. The proposed method aims to optimize the pre-synaptic weights of each post-synaptic neuron in different subpopulations using a Cooperative Co-evolutionary Differential Evolution algorithm, and employs a limited evaluation scheme where fitness evaluation is performed on a relatively small number of training instances based on fitness inheritance. We test LECCDE on three datasets with various sizes, and our results show that cooperative co-evolution significantly improves the test error comparing to standard Differential Evolution, while the limited evaluation scheme facilitates a significant reduction in computing time.

Originele taal-2Engels
TitelGECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference
UitgeverijAssociation for Computing Machinery, Inc
Aantal pagina's8
ISBN van elektronische versie9781450356183
StatusGepubliceerd - 2 jul 2018
Evenement2018 Genetic and Evolutionary Computation Conference, GECCO 2018 - Kyoto, Japan
Duur: 15 jul 201819 jul 2018


Congres2018 Genetic and Evolutionary Computation Conference, GECCO 2018

Vingerafdruk Duik in de onderzoeksthema's van 'Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolution'. Samen vormen ze een unieke vingerafdruk.

Citeer dit