Evolving Spatiotemporal Coordination in a Modular Robotic System

  • Mikhail Prokopenko
  • Vadim Gerasimov
  • Ivan Tanev
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4095)


In this paper we present a novel information-theoretic measure of spatiotemporal coordination in a modular robotic system, and use it as a fitness function in evolving the system. This approach exemplifies a new methodology formalizing co-evolution in multi-agent adaptive systems: information-driven evolutionary design. The methodology attempts to link together different aspects of information transfer involved in adaptive systems, and suggests to approximate direct task-specific fitness functions with intrinsic selection pressures. In particular, the information-theoretic measure of coordination employed in this work estimates the generalized correlation entropy K 2 and the generalized excess entropy E 2 computed over a multivariate time series of actuators’ states. The simulated modular robotic system evolved according to the new measure exhibits regular locomotion and performs well in challenging terrains.


Information Transfer Excess Entropy Multivariate Time Series Generalize Entropy Rate Entropy Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mikhail Prokopenko
    • 1
  • Vadim Gerasimov
    • 1
  • Ivan Tanev
    • 2
  1. 1.CSIRO Information and Communication Technology CentreNorth RydeAustralia
  2. 2.Department of Information Systems DesignDoshisha UniversityKyotoJapan

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