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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Detalles Bibliográficos
Main Authors: Kim, Beomjoon, Lee, Kyungjae, Lim, Sungbin, Kaelbling, Leslie, Lozano-Perez, Tomas
Formato: Artigo
Idioma:English
Publicado: Association for the Advancement of Artificial Intelligence (AAAI) 2021
Acceso en liña:https://hdl.handle.net/1721.1/132316

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