Comparing indirect encodings by evolutionary attractor analysis in the trait space of modular robots

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Abstract

In evolutionary robotics, the representation of the robot is of primary importance. Often indirect encodings are used, whereby a complex developmental process grows a body and a brain from a genotype. In this work, we aim at improving the interpretability of robot morphologies and behaviours resulting from indirect encoding. We develop and use a methodology that focuses on the analysis of evolutionary attractors, represented in what we call the trait space: Using trait descriptors defined in the literature, we define morphological and behavioural Cartesian planes where we project the phenotype of the final population. In our experiments we show that, using this analysis method, we are able to better discern the effect of encodings that differ only in minor details.

Original languageEnglish
Title of host publicationGECCO '20
Subtitle of host publicationProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages73-74
Number of pages2
ISBN (Electronic)9781450371278
DOIs
Publication statusPublished - Jul 2020
Event2020 Genetic and Evolutionary Computation Conference, GECCO 2020 - Cancun, Mexico
Duration: 8 Jul 202012 Jul 2020

Conference

Conference2020 Genetic and Evolutionary Computation Conference, GECCO 2020
CountryMexico
CityCancun
Period8/07/2012/07/20

Keywords

  • Evolutionary attractors
  • Evolutionary robotics
  • Indirect encodings

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