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Preliminary Investigations on the Evolvability of a Non spatial GasNet Model

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Advances in Artificial Life (ECAL 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4648))

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Abstract

This paper addresses the role of space in evolving a novel Non-Spatial GasNet model. It illustrates that this particular neural network model which make use of modulatory effects of diffusing gases has its evolvability improved when its neurons are not constrained to a Euclidean space. The results show that successful behaviour is achieved in fewer evaluations for the novel unconstrained GasNet than for the original model.

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Authors and Affiliations

  1. Centre for Computational Neuroscience and Robotics (CCNR), University of Sussex BN1 9QH, United Kingdom

    Patricia A. Vargas, Ezequiel A. Di Paolo & Phil Husbands

Authors
  1. Patricia A. Vargas
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  2. Ezequiel A. Di Paolo
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  3. Phil Husbands
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Editor information

Fernando Almeida e Costa Luis Mateus Rocha Ernesto Costa Inman Harvey António Coutinho

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© 2007 Springer-Verlag Berlin Heidelberg

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Vargas, P.A., Di Paolo, E.A., Husbands, P. (2007). Preliminary Investigations on the Evolvability of a Non spatial GasNet Model. In: Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey, I., Coutinho, A. (eds) Advances in Artificial Life. ECAL 2007. Lecture Notes in Computer Science(), vol 4648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74913-4_97

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  • DOI: https://doi.org/10.1007/978-3-540-74913-4_97

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74912-7

  • Online ISBN: 978-3-540-74913-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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