Abstract
In this paper, we aim to design decision-making mechanisms for an autonomous robot equipped with simple sensors, which integrates over time its perceptual experience in order to initiate a simple signalling response. Contrary to other similar studies, in this work the decision-making is uniquely controlled by the time-dependent structures of the agent’s controller, which in turn are tightly linked to the mechanisms for sensory-motor coordination. The results of this work show that a single dynamic neural network, shaped by evolution, makes an autonomous agent capable of “feeling” time through the flow of sensations determined by its actions.
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Tuci, E., Trianni, V., Dorigo, M. (2004). Evolving the “Feeling” of Time Through Sensory-Motor Coordination: A Robot Based Model. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_101
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DOI: https://doi.org/10.1007/978-3-540-30217-9_101
Publisher Name: Springer, Berlin, Heidelberg
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