Evolving artificial neural networks with FINCH

Amit Benbassat, Moshe Sipper

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

We present work with the FINCH automatic evolutionary programming tool to evolve code that generates Artificial Neural Networks (ANNs) that perform desired tasks. We show how FINCH can be used to evolve code that generates an ANN that performs a simple classifying task with proficiency.

Original languageEnglish
Title of host publicationGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion
Pages1719-1720
Number of pages2
DOIs
StatePublished - 26 Aug 2013
Event15th Annual Conference on Genetic and Evolutionary Computation, GECCO 2013 - Amsterdam, Netherlands
Duration: 6 Jul 201310 Jul 2013

Publication series

NameGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion

Conference

Conference15th Annual Conference on Genetic and Evolutionary Computation, GECCO 2013
Country/TerritoryNetherlands
CityAmsterdam
Period6/07/1310/07/13

Keywords

  • FINCH
  • Neuroevolution

ASJC Scopus subject areas

  • Computational Mathematics

Fingerprint

Dive into the research topics of 'Evolving artificial neural networks with FINCH'. Together they form a unique fingerprint.

Cite this