首页|Study Data from University of California Berkeley Provide New Insights into Robo tics and Automation (Skill-critic: Refining Learned Skills for Hierarchical Rein forcement Learning)
Study Data from University of California Berkeley Provide New Insights into Robo tics and Automation (Skill-critic: Refining Learned Skills for Hierarchical Rein forcement Learning)
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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 originating from Berkeley, C alifornia, by NewsRx correspondents, research stated, “Hierarchicalreinforcemen t learning (RL) can accelerate long-horizon decision-making by temporally abstra cting apolicy into multiple levels. Promising results in sparse reward environm ents have been seen with skills, i.e.sequences of primitive actions.”
BerkeleyCaliforniaUnited StatesNor th and Central AmericaRobotics and AutomationRoboticsEmerging TechnologiesMachine LearningReinforcement LearningUniversity of California Berkeley
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