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Mark viking (talk | contribs) →top: add basic explanation and secondary ref verifying |
Mark viking (talk | contribs) →top: I have added two sources, so removing unreferenced tag |
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{{Multiple issues|{{context|date=August 2017}}{{technical|date=August
'''Multi-Prob Cut''' is a heuristic used in [[alpha–beta pruning]] search.<ref name="Buro1997">{{cite journal |last1=Buro |first1=Michael |title=Experiments with Multi-ProbCut and a New High-Quality Evaluation Function for Othello |journal=Games in AI Research |date=1997 |pages=77-96 |url=http://citeseerx.ist.psu.edu/viewdoc/versions?doi=10.1.1.19.1136 |language=en}}</ref> The Prob Cut heuristic estimates evaluation scores at deeper levels of the search tree using a [[linear regression]] between deeper and shallower scores. Min Prob Cut extends this approach to multiple levels of the search tree. It is of particular interest in games such as [[Othello]] where there is a a strong correlation between evaluations scores at deeper and shallower levels.<ref name="Fürnkranz2001">{{cite book |last1=Fürnkranz |first1=Johannes |title=Machines that learn to play games {{!}} Guide books |date=2001 |publisher=Nova Science Publishers, Inc. |___location=Nova Science Publishers, Inc.6080 Jericho Tpke. Suite 207 Commack, NYUnited States |isbn=978-1-59033-021-0 |pages=11-59 |url=https://dl.acm.org/doi/book/10.5555/644391}}</ref>
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