A new action selection policy in reinforcement learning problems based on fuzzy mappings
محل انتشار: چهاردهمین کنفرانس سیستم های فازی ایران
سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 430
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شناسه ملی سند علمی:
ICFUZZYS14_038
تاریخ نمایه سازی: 21 اردیبهشت 1397
چکیده مقاله:
In this paper, a new policy in action selection processes related to reinforcement learning problems is presented. This policy in fact is a fuzzy mapping that attributes probabilities of selection to actions proportional to agent s view. Agent s view in this method inculcates to system by a control parameter named ξ that tunes and adjusts very simpler than τ in boltzman softmax method. Intuitiveness and interpretability of the parameter ξ because of using fuzzy system gives us opportunity to contribute the human knowledge in the action selection process. Better performance and more rapid convergence also are two other significant causes for superiority of proposed method.
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نویسندگان
Mohsen Annabestani
Ph.D. student, Department of electrical engineering, Ferdowsi University, Mashhad, Iran
Mohammad Bagher Naghibi
Assistant Professor, Department of electrical engineering, Ferdowsi University, Mashhad, Iran