Abstract
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.
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Prokopenko, M., Gerasimov, V., Tanev, I. (2006). Evolving Spatiotemporal Coordination in a Modular Robotic System. In: Nolfi, S., et al. From Animals to Animats 9. SAB 2006. Lecture Notes in Computer Science(), vol 4095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840541_46
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DOI: https://doi.org/10.1007/11840541_46
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