Now showing items 1-5 of 5

  • Jelisavcic, Milan; Kiesel, Rafael; Glette, Kyrre; Haasdijk, Evert; Eiben, AE (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2017)
    Evolving robot morphologies implies the need for lifetime learning so that newborn robots can learn to manipulate their bodies. An individual’s morphology will obviously combine traits of all its parents; it must adapt its ...
  • Miras, Karine; Haasdijk, Evert; Glette, Kyrre; Eiben, AE (Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2018)
    This paper investigates the evolution of modular robots using different selection preferences (i.e., fitness functions), aiming at novelty, speed of locomotion, number of limbs, and com- binations of these. The outcomes ...
  • Miras, Karine; Gansekoele, Arwin; Glette, Kyrre; Eiben, AE (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2018)
    In a recent study we have encountered an unexpected result regarding the evolutionary exploration of robot morphology spaces. Specifically, we found that an algorithm driven by selection based on morphological novelty ...
  • Jelisavcic, Milan; Glette, Kyrre; Haasdijk, Evert; Eiben, AE (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2019)
    We study evolutionary robot systems where not only the robot brains but also the robot bodies are evolvable. Such systems need to include a learning period right after ‘birth’ to acquire a controller that fits the newly ...
  • Miras, Karine; Haasdijk, Evert; Glette, Kyrre; Eiben, AE (Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2018)
    We present a study on morphological traits of evolved modular robots. We note that the evolutionary search space –the set of obtainable morphologies– depends on the given representation and reproduction operators and we ...