Evolving-Controllers Versus Learning-Controllers for Morphologically Evolvable Robots

Karine Miras*, Matteo De Carlo, Sayfeddine Akhatou, A. E. Eiben

*Corresponding author for this work

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

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Abstract

We investigate an evolutionary robot system where (simulated) modular robots can reproduce and create robot children that inherit the parents’ morphologies by crossover and mutation. Within this system we compare two approaches to creating good controllers, i.e., evolution only and evolution plus learning. In the first one the controller of a robot child is inherited, so that it is produced by applying crossover and mutation to the controllers of its parents. In the second one the controller of the child is also inherited, but additionally, it is enhanced by a learning method. The experiments show that the learning approach does not only lead to different fitness levels, but also to different (bigger) robots. This constitutes a quantitative demonstration that changes in brains, i.e., controllers, can induce changes in the bodies, i.e., morphologies.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computation
Subtitle of host publication23rd European Conference, EvoApplications 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings
EditorsPedro A. Castillo, Juan Luis Jiménez Laredo, Francisco Fernández de Vega
PublisherSpringer
Pages86-99
Number of pages14
ISBN (Electronic)9783030437220
ISBN (Print)9783030437213
DOIs
Publication statusPublished - 2020
Event23rd European Conference on Applications of Evolutionary Computation, EvoApplications 2020, held as part of EvoStar 2020 - Seville, Spain
Duration: 15 Apr 202017 Apr 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12104 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd European Conference on Applications of Evolutionary Computation, EvoApplications 2020, held as part of EvoStar 2020
Country/TerritorySpain
CitySeville
Period15/04/2017/04/20

Keywords

  • Evolutionary Robotics
  • Life-time learning
  • Modular robots
  • Morphological evolution

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