LinUCB applied to Monte Carlo tree search

DOI10.1016/J.TCS.2016.06.035zbMath1370.68266OpenAlexW2473144994MaRDI QIDQ307792

Tomoyuki Kaneko, Yusaku Mandai

Publication date: 5 September 2016

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2016.06.035

zbMATH Keywords

contextual banditLinUCBMCTSmulti-armed bandit problem

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Combinatorial games (91A46)

Cites Work

• Multi-armed bandits with episode context
• An analysis of alpha-beta pruning
• Best-first minimax search
• Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
• Large-Scale Optimization for Evaluation Functions with Minimax Search
• Deep Blue
• Computer Go: An AI oriented survey
• Finite-time analysis of the multiarmed bandit problem

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