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IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, VOL. 4, NO. 1, MARCHA Survey of Monte Carlo Tree Search Methods Cameron Browne, Member, IEEE, Edward Powley, Member, IEEE, Daniel Whitehouse, Memb
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Document Date: 2012-06-11 20:40:44


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City

Bandit / /

Company

Russell / E. Powley / /

Country

United Kingdom / /

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Facility

University of Bradford / Imperial College / University of Essex / /

IndustryTerm

tree search / insights into how other algorithms / decision applications / search approach / unknown law / partial search tree / maxn algorithm / search algorithm / basic algorithm / search iteration / search parameters / iterated local search / minimax search / overall search / tree-based search / game playing algorithms / search tree / numerical algorithms / proposed search method / iteratively building a search tree / /

OperatingSystem

GNU / /

Organization

Imperial College London / School of Computing / Informatics and Media / Department of Computing / University of Essex / School of Computer Science and Electronic Engineering / University of Bradford / /

Person

Philipp Rohlfshagen / Simon Lucas / Xi / ARLO T REE / Daniel Whitehouse / Stephen Tavener / Spyridon Samothrakis / Carlo Tree / Diego Perez / Game Playing / Peter I. Cowling / Simon Colton Abstract / Edward Powley / /

Position

current player / champion Hex player / AI researcher / General / Player / Single-Player / puzzle designer / /

Product

Pentax K-x Digital Camera / /

RadioStation

Work 7.2 / /

Technology

4.2 Bandit Algorithm / specific algorithm / maxn algorithm / 3.1 The UCT algorithm / MCTS algorithm / basic MCTS algorithm / UCT algorithm / 2012 Algorithm / AI game playing algorithms / 2 The UCT algorithm / proposed algorithm / artificial intelligence / 3.1 Algorithm / Monte Carlo search algorithm / simulation / Digital Object Identifier / basic algorithm / be approximated using random simulation / /

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