Comparison of genetic algorithm and particle swarm optimizer when evolving a recurrent neural network

Authors:
Matthew Settles;Brandon Rodebaugh;Terence Soule
Affiliations:
Department of Computer Science, University of Idaho, Moscow, Idaho;Department of Computer Science, University of Idaho, Moscow, Idaho;Department of Computer Science, University of Idaho, Moscow, Idaho
Venue:
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Year:
2003

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Abstract

This paper compares the performance of GAs and PSOs in evolving weights of a recurrent neural network. The algorithms are tested on multiple network topologies. Both algorithms produce successful networks. The GA is more successful evolving larger networks and the PSO is more successful on smaller networks.