Autonomous Robots

, Volume 11, Issue 3, pp 311–317 | Cite as

Evolution of Plastic Control Networks

  • Dario Floreano
  • Joseba Urzelai


Evolutionary Robotics is a powerful method to generate efficient controllers with minimal human intervention, but its applicability to real-world problems remains a challenge because the method takes long time and it requires software simulations that do not necessarily transfer smoothly to physical robots. In this paper we describe a method that overcomes these limitations by evolving robots for the ability to adapt on-line in few seconds. Experiments show that this method require less generations and smaller populations to evolve, that evolved robots adapt in a few seconds to unpredictable change-including transfers from simulations to physical robots- and display non-trivial behaviors. Robots evolved with this method can be dispatched to other planets and to our homes where they will autonomously and quickly adapt to the specific properties of their environments if and when necessary.

evolutionary robotics neural networks evolution and learning 


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Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Dario Floreano
    • 1
  • Joseba Urzelai
    • 2
  1. 1.Institute of Robotic SystemsSwiss Federal Institute of Technology (EPFL)LausanneSwitzerland
  2. 2.ELCA Informatique SALausanneSwitzerland

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