Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds

Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds

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<jats:p>Many important applications, including robotics, data-center management, and process control, require planning action sequences in domains with continuous state and action spaces and discontinuous objective functions. Monte Carlo tree search (MCTS) is an effective strategy for planning...

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Bibliographic Details
Main Authors: Kim, Beomjoon, Lee, Kyungjae, Lim, Sungbin, Kaelbling, Leslie P, Lozano-Perez, Tomas
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:English
Published: Association for the Advancement of Artificial Intelligence (AAAI) 2022
Online Access:https://hdl.handle.net/1721.1/132316.2

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