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Integrating Evolutionary Game-Theoretical Methods and Deep Reinforcement Learning for Adaptive Strategy Optimization in User-Side Electricity Markets: A Comprehensive Review.

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Title: Integrating Evolutionary Game-Theoretical Methods and Deep Reinforcement Learning for Adaptive Strategy Optimization in User-Side Electricity Markets: A Comprehensive Review.
Authors: Cheng, Lefeng1 (AUTHOR) chenglefeng@gzhu.edu.cn, Wei, Xin1 (AUTHOR), Li, Manling1 (AUTHOR), Tan, Can1 (AUTHOR), Yin, Meng1 (AUTHOR), Shen, Teng1 (AUTHOR) shent215@gzhu.edu.cn, Zou, Tao1 (AUTHOR) shent215@gzhu.edu.cn
Source: Mathematics (2227-7390). Oct2024, Vol. 12 Issue 20, p3241. 56p.
Database: Academic Search Ultimate
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  Data: Integrating Evolutionary Game-Theoretical Methods and Deep Reinforcement Learning for Adaptive Strategy Optimization in User-Side Electricity Markets: A Comprehensive Review.
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  Data: <searchLink fieldCode="JN" term="%22Mathematics+%282227-7390%29%22">Mathematics (2227-7390)</searchLink>. Oct2024, Vol. 12 Issue 20, p3241. 56p.
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RecordInfo BibRecord:
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        Value: 10.3390/math12203241
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        Text: English
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      – TitleFull: Integrating Evolutionary Game-Theoretical Methods and Deep Reinforcement Learning for Adaptive Strategy Optimization in User-Side Electricity Markets: A Comprehensive Review.
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            NameFull: Wei, Xin
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            NameFull: Shen, Teng
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              Text: Oct2024
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              Y: 2024
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