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- W3017225295 abstract "This paper proposes a new swarm reinforcement learning technique and its application to operational planning of energy plants (OPEPs) in buildings and factories. The proposed technique is differential evolutionary particle swarm optimization based q-learning with advantage (DEEPSO-Q w/A). The proposed DEEPSO-Q w/A based method can reduce engineering man-hour to develop the planning system and operational costs of the system. The results of the proposed method are compared with those of the conventional PSO-Q and DEEPSO-Q based methods. It is verified that the proposed method can reduce energy costs the most among the three applied methods." @default.
- W3017225295 created "2020-04-24" @default.
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- W3017225295 date "2020-02-01" @default.
- W3017225295 modified "2023-10-14" @default.
- W3017225295 title "Swarm Reinforcement Learning using DEEPSO-Q with Advantage for Operational Planning of Energy Plants" @default.
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- W3017225295 doi "https://doi.org/10.1109/icaiic48513.2020.9065286" @default.
- W3017225295 hasPublicationYear "2020" @default.
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