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hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorCazenave, Tristan
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorNegrevergne, Benjamin
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorSikora, Florian
HAL ID: 742949
ORCID: 0000-0003-2670-6258
dc.date.accessioned2021-10-22T13:03:48Z
dc.date.available2021-10-22T13:03:48Z
dc.date.issued2020
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22089
dc.language.isoenen
dc.subjectMonte Carloen
dc.subject.ddc005en
dc.titleMonte Carlo Graph Coloringen
dc.typeCommunication / Conférence
dc.description.abstractenGraph Coloring is probably one of the most studied and famous problem in graph algorithms. Exact methods fail to solve instances with more than few hundred vertices, therefore, a large number of heuristics have been proposed. Nested Monte Carlo Search (NMCS) and Nested Rollout Policy Adaptation (NRPA) are Monte Carlo search algorithms for single player games. Surprisingly, few work has been dedicated to evaluating Monte Carlo search algorithms to combinatorial graph problems. In this paper we expose how to efficiently apply Monte Carlo search to Graph Coloring and compare this approach to existing ones.en
dc.identifier.citationpages100-115en
dc.relation.ispartoftitleMonte Carlo Searchen
dc.relation.ispartofeditorCazenave, Tristan
dc.relation.ispartofeditorTeytaud, Olivier
dc.relation.ispartofeditorWinands, Mark H. M.
dc.relation.ispartofpublnameSpringeren
dc.relation.ispartofurl10.1007/978-3-030-89453-5en
dc.subject.ddclabelProgrammation, logiciels, organisation des donnéesen
dc.relation.ispartofisbn978-3-030-89453-5en
dc.relation.conftitleFirst Workshop, MCS 2020, Held in Conjunction with IJCAI 2020en
dc.relation.confdate2021-01
dc.relation.confcityvirtuelen
dc.relation.forthcomingnonen
dc.identifier.doi10.1007/978-3-030-89453-5_8en
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2021-10-22T12:56:55Z
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