Robotics & Machine Learning Daily News2024,Issue(MAY.15) :60-61.

Studies from Chinese Academy of Sciences Update Current Data on Computational In telligence (Fm3q: Factorized Multi-agent Minimax Q-learning for Two-team Zero-su m Markov Game)

Robotics & Machine Learning Daily News2024,Issue(MAY.15) :60-61.

Studies from Chinese Academy of Sciences Update Current Data on Computational In telligence (Fm3q: Factorized Multi-agent Minimax Q-learning for Two-team Zero-su m Markov Game)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing - Computational Intelligence have been published. According to news reportin g out of Beijing, People’s Republic of China, by NewsRx editors, research stated , “Many real-world applications involve some agents that fall into two teams, wi th payoffs that are equal within the same team but of opposite sign across the o pponent team. The so-called twoteam zero-sum Markov games (2t0sMGs) can be reso lved with reinforcement learning in recent years.”

Key words

Beijing/People’s Republic of China/Asi a/Computational Intelligence/Emerging Technologies/Machine Learning/Reinforc ement Learning/Chinese Academy of Sciences

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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