Benefits of Lamarckian Evolution for Morphologically Evolving Robots

Milan Jelisavcic, Rafael Kiesel, Kyrre Glette, Evert Haasdijk, A.E. Eiben

Research output: Contribution to ConferencePosterOther research output

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Abstract

Implementing lifetime learning by means of on-line evolution, we establish an indirect encoding scheme that combines Compositional Pattern Producing Networks (CPPNs) and Central Pattern Generators (CPGs) as a relevant learner and controller for open-loop gait controllers in modular robots which have evolving morphologies. Experimental validation on the morphologically evolved robots shows that a Lamarckian setup with CPPN-CPG provides substantial benefits compared to controllers learned from scratch.
Original languageEnglish
Number of pages2
DOIs
Publication statusAccepted/In press - Jul 2017
EventThe Genetic and Evolutionary Computation Conference - Germany, Berlin, Germany
Duration: 15 Jul 201719 Jul 2017
Conference number: 18
http://gecco-2017.sigevo.org/index.html/HomePage

Conference

ConferenceThe Genetic and Evolutionary Computation Conference
Abbreviated titleGECCO 2017
CountryGermany
CityBerlin
Period15/07/1719/07/17
Internet address

Keywords

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

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