If it evolves it needs to learn

A. E. Eiben, Emma Hart

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


We elaborate on (future) evolutionary robot systems where morphologies and controllers of real robots are evolved in the real-world. We argue that such systems must contain a learning component where a newborn robot refines its inherited controller to align with its body, which will inevitably be different from its parents.

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
Number of pages2
ISBN (Electronic)9781450371278
Publication statusPublished - Jul 2020
Event2020 Genetic and Evolutionary Computation Conference, GECCO 2020 - Cancun, Mexico
Duration: 8 Jul 202012 Jul 2020


Conference2020 Genetic and Evolutionary Computation Conference, GECCO 2020


  • Evolutionary robotics
  • Lamarckian evolution
  • Online learning

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