Abstract
A fuzzy multi-objective control problem has been handled in many different ways such as neural network and reinforcement learning etc. Among them, reinforcement learning solves a fuzzy multi-objective control problem without any priori knowledge about an environment. In this paper, a new method of reinforcement learning for a fuzzy multi-objective control problem is proposed in consideration of newly defined objective TD( λ ), where TD stands for a temporal difference. The proposed method reformulates a fuzzy multiobjective control problem into a problem similar to a reinforcement learning problem under non-Markov environment, where objective eligibility is considered for handling multi-rewards, similarly as TD( λ ) is applied to a reinforcement learning problem under a non-Markov environment.
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References
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© 2002 Springer-Verlag Berlin Heidelberg
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Myung, HC., Bien, Z.Z. (2002). Similarity between Fuzzy Multi-objective Control and Eligibility. In: Pal, N.R., Sugeno, M. (eds) Advances in Soft Computing — AFSS 2002. AFSS 2002. Lecture Notes in Computer Science(), vol 2275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45631-7_12
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DOI: https://doi.org/10.1007/3-540-45631-7_12
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Online ISBN: 978-3-540-45631-5
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