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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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
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