Study Data from University of Virginia Provide New Insights into Robotics and Au tomation (Safe Pomdp Online Planning Among Dynamic Agents Via Adaptive Conformal Prediction)

Robotics & Machine Learning Daily News2024，Issue(Nov.6) ：26-26.

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Study Data from University of Virginia Provide New Insights into Robotics and Au tomation (Safe Pomdp Online Planning Among Dynamic Agents Via Adaptive Conformal Prediction)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics - Robotics and Automation.According to news reporting originating in C harlottesville, Virginia, by NewsRx journalists, research stated, “Online planni ng for partially observable Markov decision processes (POMDPs) provides efficien t techniques for robot decision-making under uncertainty.However, existing meth ods fall short of preventing safety violations in dynamic environments.”

Key words

Charlottesville/Virginia/United States/North and Central America/Robotics and Automation/Robotics/University of Vi rginia

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出版年

2024

Robotics & Machine Learning Daily News

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