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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10445/8450

タイトル: Adaptive Nutrient Water Supply Control of Plant Factory System by Reinforcement Learning
著者: Wakahara, Takumi
MIKAMI, Sadayoshi
アブストラクト: An adaptive nutrient control method for a plant factory is proposed. The method is based on a Reinforcement Learning modified for a target in which one state never comes back during a single episode and a reward is given after a very long delay. In application such as plant growth control, one episode takes a very long time period, and a rapid convergence to a prospective control solution is essential, whilst an extensive exploration is needed since there is usually no precise model available. A method like Reinforcement Learning is useful for a problem having no reference model. But a necesity of exploration does not match the need for rapid convergence, and a new balancing method is needed. In this research, an avarage reward distribution method is proposed, which is similar to the Profit Sharing method but affects more extensively to find much prospective early solutions, whilst guaranteeing to converge into a rational solution in a long run. An experiment is conducted in a simple plant factory system, which shows that at least standard Reinforcement Learning is insufficient for this type of problem. Computer simulations show that the method has good effects comparing to a standard RL, and a profit sharing method.
研究業績種別: 原著論文/Original Paper
資料種別: Journal Article
査読有無: あり/yes
単著共著: 共著/joint
発表雑誌名,発表学会名など: Journal of Advanced Computational Intelligence and Intelligent Informatics
巻: 15
号: 7
開始ページ: 831
終了ページ: 837
年月日: 2011年9月
出版社: Fuji Technology Press
出現コレクション:三上 貞芳


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