Integration of Evolution with a Robot Action Selection Model

  • Fernando Montes-González
  • José Santos Reyes
  • Homero Ríos Figueroa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4293)


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.


Mobile Robot Action Selection Obstacle Avoidance Real Robot Perceptual Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fernando Montes-González
    • 1
  • José Santos Reyes
    • 2
  • Homero Ríos Figueroa
    • 1
  1. 1.Facultad de Física e Inteligencia ArtificialUniversidad VeracruzanaXalapa, Ver.México
  2. 2.Departamento de Computación, Facultad de InformáticaUniversidade da CoruñaCoruña

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