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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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
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