A new action selection policy in reinforcement learning problems based on fuzzy mappings

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.

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