Formation of spatial representations in evolving autonomous robots

In this paper we describe how a population of evolving robots can autonomously develop forms of spatial representation that allow them to discriminate different locations of their environment. Developed representation forms consist of patterns of activations of internal neurons that are generated by integrating sequences of sensory-motor states while the robots interact autonomously with their environment. Moreover, these representation forms are allocentric, i.e. they allow evolved robots to identify a given spatial location independently from the robots' initial position and orientation in the environment. The analysis on the robots' representation system indicate that it can be characterized as a limit cycle resulting from the transient dynamic between fixed attractor points that alternate while the robot move in the environment. We also demonstrate how the evolved representation systems display remarkable generalization properties. We conclude the paper by discussing the characteristics of the representation system developed by the robots and its relation with other models described in the literature

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