首页|Data on Robotics and Automation Reported by Researchers at Carnegie Mellon Unive rsity (Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning In Autonomous Driving)
Data on Robotics and Automation Reported by Researchers at Carnegie Mellon Unive rsity (Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning In Autonomous Driving)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Current study results on Robotics - Ro botics and Automation have been published. According to news reporting originati ng in Pittsburgh, Pennsylvania, by NewsRx journalists, research stated, “In the domain of autonomous driving, the offline Reinforcement Learning (RL) approaches exhibit notable efficacy in addressing sequential decision-making problems from offline datasets. However, maintaining safety in diverse safety-critical scenar ios remains a significant challenge due to long-tailed and unforeseen scenarios absent from offline datasets.”
PittsburghPennsylvaniaUnited StatesNorth and Central AmericaRobotics and AutomationRoboticsEmerging Technolo giesMachine LearningReinforcement LearningCarnegie Mellon University
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