Robotics & Machine Learning Daily News2024,Issue(Jul.12) :40-40.

Researchers’ Work from Stanford University Focuses on Robotics and Automation (D istributed Online Planning for Min-max Problems In Networked Markov Games)

Robotics & Machine Learning Daily News2024,Issue(Jul.12) :40-40.

Researchers’ Work from Stanford University Focuses on Robotics and Automation (D istributed Online Planning for Min-max Problems In Networked Markov Games)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ro botics - Robotics and Automation. Accordingto news reporting originating from S tanford, California, by NewsRx correspondents, research stated,“Min-max problem s are important in multi-agent sequential decision-making because they improve t heperformance of the worst-performing agent in the network. However, solving th e multi-agent min-maxproblem is challenging.”

Key words

Stanford/California/United States/Nor th and Central America/Robotics and Automation/Robotics/Stanford University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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