SISL
@sislaboratory
Stanford Intelligent Systems Laboratory, Aeronautics & Astronautics Department. Advancing Research on Autonomous Systems and Decision Making Under Uncertainty.
ID: 3686552064
http://sisl.stanford.edu 25-09-2015 23:41:45
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We introduce history-dependent dual variables in Lagrangian-guided MCTS to tackle myopic action selection in CPOMDPs. Discover recent work by Paula Stocco, Suhas Chundi, Arec Jamgochian, and Mykel Kochenderfer: youtube.com/watch?v=yCZCk7…