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Efficient Evolution Strategies for Exploration in mobile robotics

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Evolutionary Computing (AISB EC 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1143))

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Abstract

This paper focuses on the evaluation of a number of recently defined Evolution Strategy operators applied to a novel and challenging environment. The ES operates as the exploration component of a hybrid learning architecture for mobile robotics. In this on-line application both the population and number of generations must be small. Further, the objective function is multi-modal and dynamic, i.e. changing shape within and between generations. The results of our preliminary experiments indicate that derandomised mutation and intermediate recombination operators gave the best performance, especially with very small populations.

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Authors and Affiliations

  1. Intelligent Autonomous Systems Engineering Laboratory Faculty of Engineering, University of the West of England, Coldharbour Lane, BS16 1QY, Frenchay, Bristol, UK

    J. C. W. Sullivan & A. G. Pipe

Authors
  1. J. C. W. Sullivan
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  2. A. G. Pipe
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Editor information

Terence C. Fogarty

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© 1996 Springer-Verlag Berlin Heidelberg

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Sullivan, J.C.W., Pipe, A.G. (1996). Efficient Evolution Strategies for Exploration in mobile robotics. In: Fogarty, T.C. (eds) Evolutionary Computing. AISB EC 1996. Lecture Notes in Computer Science, vol 1143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032780

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  • DOI: https://doi.org/10.1007/BFb0032780

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61749-5

  • Online ISBN: 978-3-540-70671-7

  • eBook Packages: Springer Book Archive

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