On-line Evolution of Foraging Behaviour in a Population of Real Robots

  • Jacqueline HeinermanEmail author
  • Alessandro Zonta
  • Evert Haasdijk
  • A. E. Eiben
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9598)


This paper describes a study in evolutionary robotics conducted completely in hardware without using simulations. The experiments employ on-line evolution, where robot controllers evolve on-the-fly in the robots’ environment as the robots perform their tasks. The main issue we consider is the feasibility of tackling a non-trivial task in a realistic timeframe. In particular, we investigate whether a population of six robots can evolve foraging behaviour in one hour. The experiments demonstrate that this is possible and they also shed light on some of the important features of our evolutionary system. Further to the specific results we also advocate the system itself. It provides an example of a replicable and affordable experimental set-up for other researches to engage in research into on-line evolution in a population of real robots.


Evolutionary robotics Neural networks Distributed on-line learning Embodied evolution Foraging 



This work was made possible by the European Union FET Proactive Initiative Knowing, Doing, Being: Cognition Beyond Problem Solving, funding the Deferred Restructuring of Experience in Autonomous Machines (DREAM) project under grant agreement 640891.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jacqueline Heinerman
    • 1
    Email author
  • Alessandro Zonta
    • 2
  • Evert Haasdijk
    • 1
  • A. E. Eiben
    • 1
  1. 1.Vrije Universiteit AmsterdamAmsterdamThe Netherlands
  2. 2.University of PaduaPaduaItaly

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