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 E2 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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Prokopenko, M., Gerasimov, V., & Tanev, I. (2006). Evolving spatiotemporal coordination in a modular robotic system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4095 LNAI, pp. 558–569). Springer Verlag. https://doi.org/10.1007/11840541_46
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