Abstract
Complex “lifelike” behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, “flocking” and “arrangement” of multiple autonomouse mobile robots are represented by a small number of fuzzy rules. Fuzzy rules in Sugeno type and their related parameters are automatically generated from clustering input-output data obtained from the algorithms for the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.
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© 2005 Springer-Verlag Berlin Heidelberg
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Kim, JH., Park, JB., Yang, HS., Park, YP. (2005). Generation of Fuzzy Rules and Learning Algorithms for Cooperative Behavior of Autonomouse Mobile Robots(AMRs). In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_126
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DOI: https://doi.org/10.1007/11539506_126
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28312-6
Online ISBN: 978-3-540-31830-9
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