Evolutionary predator-prey robot systems: From simulation to real world

Gongjin Lan, Jiunhan Chen, A. E. Eiben

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Abstract

We present a feasibility study on evolving controllers for a group of wheeled robot predators that need to capture a prey robot. Our solution method works by evolving controllers in simulation for 100 generations, followed by 10 generations on real robots. The best controllers are further evaluated by their sensitivity for the initial positions. The results demonstrate the practical feasibility of this approach and give an indication of the time required to develop good solutions for the predator-prey problem.

Original languageEnglish
Title of host publicationGECCO '19
Subtitle of host publicationProceedings of the Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages123-124
Number of pages2
ISBN (Electronic)9781450367486
DOIs
Publication statusPublished - 13 Jul 2019
Event2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019

Publication series

NameGECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion

Conference

Conference2019 Genetic and Evolutionary Computation Conference, GECCO 2019
Country/TerritoryCzech Republic
CityPrague
Period13/07/1917/07/19

Keywords

  • Evolutionary robotics
  • Predator-prey system
  • Reality Gap

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