Major feedback loops supporting artificial evolution in multi-modular robotics

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Abstract

In multi-modular reconfigurable robotics it is extremely challenging to develop control software that is able to generate robust but still flexible behavior of the 'robotic organism' that is formed by several independent robotic modules. We propose artificial evolution and self-organization as methodologies to develop such control software. In this article, we present our concept to evolve a self-organized multi-modular robot. We decompose the network of feedbacks, that affect the evolutionary pathway and show why and how specific sub-components, which are involved in these feedbacks, should be subject of evolutionary adaptation. Self-organization is a major component of our framework and is implemented by a hormone-inspired controller governing the behavior of singular autonomous modules. We show first results, which were obtained by artificial evolution with our framework, and give an outlook of how the framework will be applied in future research. © 2011 Springer-Verlag Berlin Heidelberg.

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Schmickl, T., Stradner, J., Hamann, H., Winkler, L., & Crailsheim, K. (2011). Major feedback loops supporting artificial evolution in multi-modular robotics. In Studies in Computational Intelligence (Vol. 341, pp. 195–209). https://doi.org/10.1007/978-3-642-18272-3_13

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