首页|Recent Findings from University of Technology Sydney Has Provided New Informatio n about Robotics (Deep Reinforcement Learning In Nonstationary Environments With Unknown Change Points)

Recent Findings from University of Technology Sydney Has Provided New Informatio n about Robotics (Deep Reinforcement Learning In Nonstationary Environments With Unknown Change Points)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics have been published. According to news reporting originating in Ultimo, Australia, b y NewsRx journalists, research stated, “Deep reinforcement learning (DRL) is a p owerful tool for learning from interactions within a stationary environment wher e state transition and reward distributions remain constant throughout the proce ss. Addressing the practical but challenging nonstationary environments with tim e-varying state transition or reward function changes during the interactions, i ngenious solutions are essential for the stability and robustness of DRL agents. ”

UltimoAustraliaAustralia and New Zea landEmerging TechnologiesMachine LearningNano-robotReinforcement Learnin gRoboticsUniversity of Technology Sydney

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Mar.15)