Abstract
Autonomous Robots Systems (ARS) can learn by establishing plans, executing them in a given environment and analyzing the results of the execution. The logic used among this process is usually the classic logic, which most of the times ends up being too restrictive and not consistent with the world the ARS is facing. This paper proposes the application of fuzzy logic to address this issue and improve the ARS learning curve considerably.
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References
Ierache, J., Garcia Martinez, R., De Giusti, A.: Learning Life Cycle in Autonomous Robots Systems. In: Bramer, M. (ed.) Artificial Intelligence and Practice II. IFIP, vol. 276, pp. 451–455. Springer, Boston (2008)
Ierache, J., García-Martínez, R., De Giusti, A.: Learning by collaboration in intelligent autonomous systems. In: Bramer, M. (ed.) IFIP AI 2010. IFIP AICT, vol. 331, pp. 143–152. Springer, Heidelberg (2010)
García-Martínez, R., Borrajo, D.: Planning, learning, and executing in autonomous systems. In: Steel, S. (ed.) ECP 1997. LNCS (LNAI), vol. 1348, pp. 208–220. Springer, Heidelberg (1997)
García Martínez, R., Borrajo, D.: An Integrated Approach of Learning, Planning and Executing. Journal of Robots and Robotic Systems 29, 47–78 (2000)
García-Martínez, R., Borrajo, D., Maceri, P., Britos, P.: Learning by knowledge sharing in autonomous intelligent systems. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds.) IBERAMIA–SBIA 2006. LNCS (LNAI), vol. 4140, pp. 128–137. Springer, Heidelberg (2006)
Matellan, V., Fernandez, C., Molina, J.: Genetic learning of fuzzy reactive controllers. Robotics and Autonomous Systems 25, 33–41 (1998)
E-Puck, “Robot e-puck”, web (2012), http://www.e-puck.org/
Webots, “Simulador Webots”, web (2012), http://www.cyberbotics.com/
Braitenberg, V.: Vehicles: Explorations In Synthetic Psychology. MIT Press (1984)
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González, M.L., Ierache, J.S. (2013). Application of Fuzzy Logic in Learning Autonomous Robots Systems. In: Kim, JH., Matson, E., Myung, H., Xu, P. (eds) Robot Intelligence Technology and Applications 2012. Advances in Intelligent Systems and Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37374-9_32
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DOI: https://doi.org/10.1007/978-3-642-37374-9_32
Publisher Name: Springer, Berlin, Heidelberg
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