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MCαβ
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'''Monte-Carlo Alpha-Beta''', '''(MCαβ)'''<br/>
is a [[Best-First|Best-First search]] algorithm based on [[Monte-Carlo Tree Search]] and a shallow [[Alpha-Beta|alpha-beta]] [[Depth-First|depth-first-search]]. It is used in [[Lines of Action]] and in conjunction with [[UCT]] (Upper Confidence bounds applied to Trees) also in Chess. It is similar to the the [[Best-First Minimax Search|Best-first minimax search]] proposed by [[Richard Korf]] and [[Max Chickering]] <ref>[[Richard Korf]], [[Max Chickering]] ('''1996'''). ''[https://www.microsoft.com/en-us/research/publication/best-first-minimax-search/ Best-First Minimax Search]''. [https://en.wikipedia.org/wiki/Artificial_Intelligence_(journal) Artificial Intelligence], Vol. 84, No 1-2</ref>, one distinction between the two might be that MCTS uses usually win/draw/loss scores and BestFirst a score from a heuristic evaluation function.
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