Abstract
The development of an effective central model of action selection has already been reviewed in previous work. The central model has been set to resolve a foraging task with the use of heterogeneous behavioral modules. In contrast to collecting/depositing modules that have been hand-coded, modules related to exploring follow an evolutionary approach. However, in this paper we focus on the use of genetic algorithms for evolving the weights related to calculating the urgency for a behavior to be selected. Therefore, we aim to reduce the number of decisions made by a human designer when developing the neural substratum of a central selection mechanism.
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Montes-González, F., Reyes, J.S., Figueroa, H.R. (2006). Integration of Evolution with a Robot Action Selection Model. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_111
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DOI: https://doi.org/10.1007/11925231_111
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