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dc.contributor.authorCazenave, Tristan
dc.contributor.authorSaffidine, Abdallah
dc.contributor.authorSchofield, Michael John
dc.contributor.authorThielscher, Michael
dc.date.accessioned2017-01-16T11:31:11Z
dc.date.available2017-01-16T11:31:11Z
dc.date.issued2016
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16165
dc.language.isoenen
dc.subjectMonte Carlo Tree Search
dc.subject.ddc006en
dc.titleNested Monte Carlo Search for Two-Player Games
dc.typeCommunication / Conférence
dc.description.abstractenThe use of the Monte Carlo playouts as an evaluation function has proved to be a viable, general technique for searching intractable game spaces. This facilitate the use of statistical techniques like Monte Carlo Tree Search (MCTS), but is also known to require significant processing overhead. Weseek to improve the quality of information extracted from the Monte Carlo playout in three ways. Firstly, by nesting the evaluation function inside another evaluation function; secondly, by measuring and utilising the depth of the playout; and thirdly, by incorporating pruning strategies that eliminateunnecessary searches and avoid traps. Our experimental data, obtained on a variety of two-player games from past General Game Playing (GGP) competitions and others, demonstrate the usefulness of these techniques in a Nested Player when pitted against a standard, optimised UCT player.
dc.identifier.citationpages687-693
dc.relation.ispartoftitleProceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16)
dc.relation.ispartofeditorDale Schuurmans, Michael Wellman
dc.relation.ispartofpublnameAAAI Press
dc.relation.ispartofpublcityPalo Alto (USA)
dc.relation.ispartofdate2016
dc.subject.ddclabelMéthodes informatiques spécialesen
dc.relation.ispartofisbn978-1-57735-760-5
dc.relation.forthcomingnonen
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2017-01-23T09:50:45Z
hal.person.labIds989
hal.person.labIds107214
hal.person.labIds107214
hal.person.labIds107214
hal.identifierhal-01436286*


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