Abstract
This paper is about the design of an artificial neural network to control an autonomous robot that is required to iteratively solve a discrimination task based on time-dependent structures. The “decision making” aspect demands the robot “to decide”, during a sequence of trials, whether or not the type of environment it encounters allows it to reach a light bulb located at the centre of a simulated world. Contrary to other similar studies, in this work the robot employs environmental structures to iteratively make its choice, without previous experience disrupting the functionality of its decision-making mechanisms.
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© 2005 Springer-Verlag Berlin Heidelberg
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Tuci, E., Ampatzis, C., Dorigo, M. (2005). Evolving Neural Mechanisms for an Iterated Discrimination Task: A Robot Based Model. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_24
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DOI: https://doi.org/10.1007/11553090_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28848-0
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