ウエダ　リュウイチ   Ueda Ryuichi   上田　隆一    所属   千葉工業大学  先進工学部 未来ロボティクス学科    千葉工業大学  工学研究科 工学専攻    千葉工業大学  先進工学研究科 未来ロボティクス専攻    職種   教授
言語種別	英語
発行・発表の年月	2016/07
形態種別	国際会議プロシーディングス
査読	査読あり
標題	Particle Filter on Episode for Learning Decision Making Rule
執筆形態	共著
掲載誌名	Proc. of The 14th International Conference on Intelligent Autonomous Systems
掲載区分	国外
著者・共著者	Ryuichi Ueda, Kotaro Mizuta, Hiroshi Yamakawa and Hiroyuki Okada
概要	We propose a novel method, a particle filter on episode, for decision makings of agents in the real world. This method is used for simulating behavioral experiments of rodents as a workable model, and for decision making of actual robots. Recent studies on neuroscience suggest that hippocampus and its surroundings in brains of mammals are related to solve navigation problems, which are also essential in robotics. The hippocampus also handle memories and some parts of a brain utilize them for decision. The particle filter gives a calculation model of decision making based on memories. In this paper, we have verified that this method learns two kinds of tasks that have been frequently examined in behavioral experiments of rodents. Though the tasks have been different in character from each other, the algorithm has been able to make an actual robot take appropriate behavior in the both tasks with an identical parameter set.