The role of non-linearity for evolved multifunctional robot behavior

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Abstract

In this paper the role of non-linear control structures for the development of multifunctional robot behavior in a self-organized way is discussed. This discussion is based on experiments where combinations of two behavioral tasks are incrementally evolved. The evolutionary experiments develop recurrent neural networks of general type in a systematically way. The resulting networks are investigated according to the underlying structure-function relations. These investigations point to necessary properties providing multifunctionality, scalability, and open-ended evolutionary strategies in Evolutionary Robotics. © Springer-Verlag Berlin Heidelberg 2005.

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Hülse, M., Wischmann, S., & Pasemann, F. (2005). The role of non-linearity for evolved multifunctional robot behavior. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3637 LNCS, pp. 108–118). Springer Verlag. https://doi.org/10.1007/11549703_11

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