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Graph theory / Search algorithms / Game theory / Computer chess / Combinatorial game theory / Minimax / Reinforcement learning / Expectiminimax tree / Negamax / Mathematics / Game artificial intelligence / Artificial intelligence


Document Date: 2012-02-26 02:26:19

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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 / /

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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