Acquiring moving skills in robots with evolvable morphologies: Recent results and outlook

M. Jelisavcic, E. Haasdijk, A.E. Eiben

Research output: Chapter in Book / Report / Conference proceedingChapterAcademic

Abstract

© 2017 ACM. We construct and investigate a strongly embodied evolutionary system, where not only the controllers but also the morphologies undergo evolution in an on-line fashion. In these studies, we have been using various types of robot morphologies and controller architectures in combination with several learning algorithms, e.g. evolutionary algorithms, reinforcement learning, simulated annealing, and HyperNEAT. This hands-on experience provides insights and helps us elaborate on interesting research directions for future development.
Original languageEnglish
Title of host publicationGECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion
Pages1735-1741
Number of pages7
ISBN (Electronic)9781450349390
DOIs
Publication statusPublished - 2017

Publication series

NameGECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion

Keywords

  • Evolutionary robotics
  • Gait learning
  • Indirect encoding
  • Lamarckian evolution
  • On-line evolution

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    Jelisavcic, M., Haasdijk, E., & Eiben, A. E. (2017). Acquiring moving skills in robots with evolvable morphologies: Recent results and outlook. In GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1735-1741). (GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion). https://doi.org/10.1145/3067695.3084200