Comparing encodings for performance and phenotypic exploration in evolving modular robots

Frank Veenstra, Emma Hart, Edgar Buchanan, Wei Li, Matteo De Carlo, Agoston E. Eiben

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Abstract

To investigate how encodings influence evolving the morphology and control of modular robots, we compared three encodings: a direct encoding and two generative encodings-a compositional pattern producing network (CPPN) and a Lindenmayer System (L-System). The evolutionary progression and final performance of the direct encoding and the L-System was significantly better than the CPPN. The generative encodings converge quicker than the direct encoding in terms of morphological and controller diversity.

Original languageEnglish
Title of host publicationGECCO '19
Subtitle of host publicationProceedings of the Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages127-128
Number of pages2
ISBN (Electronic)9781450367486
DOIs
Publication statusPublished - Jul 2019
Event2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019

Conference

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

Funding

This project has received funding from "Autonomous Robot Evolution: Cradle To Grave", EPSRC reference: EP/R035733/1.

FundersFunder number
Engineering and Physical Sciences Research CouncilEP/R035733/1
Engineering and Physical Sciences Research Council

    Keywords

    • Encodings
    • Evolutionary Robotics

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