@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00927252v1> a dcat:Dataset ;
    dct:description """
              In this thesis, I studied sequential decision making problems, with a focus on the unit commitment problem. Traditionnaly solved by dynamic programming methods, this problem is still a challenge, due to its high dimension and to the sacrifices made on the accuracy of the model to apply state of the art methods. I investigated on the applicability of Monte Carlo Tree Search methods for this problem, and other problems that are single player, stochastic and continuous sequential decision making problems. In doing so, I obtained a consistent and anytime algorithm, that can easily be combined with existing strong heuristic solvers.
            """ ;
    dct:identifier "tel-00927252" ;
    dct:issued "2026-05-07T13:16:43.358029"^^xsd:dateTime ;
    dct:language "en" ;
    dct:modified "2026-05-07T13:16:43.358035"^^xsd:dateTime ;
    dct:publisher <https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> ;
    dct:title "Monte Carlo Tree Search for Continuous and Stochastic Sequential Decision Making Problems" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "CCSD" ] ;
    dcat:distribution <https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00927252v1/resource/55d479e9-b6ba-47eb-b2d6-f29c3f2168e1> ;
    dcat:keyword "apprentissage-par-renforcement",
        "energie",
        "energy",
        "infoeu-reposemanticsdoctoralthesis",
        "infoinfo-dscomputer-science-csdata-structures-and-algorithms-csds",
        "infoinfo-gtcomputer-science-cscomputer-science-and-game-theory-csgt",
        "infoinfo-lgcomputer-science-csmachine-learning-cslg",
        "optimisation",
        "optimization",
        "reinforcement-learning",
        "theses" ;
    dcat:landingPage <https://theses.hal.science/tel-00927252> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00927252v1/resource/55d479e9-b6ba-47eb-b2d6-f29c3f2168e1> a dcat:Distribution ;
    dct:format "HTML" ;
    dct:issued "2026-05-07T13:16:43.365943"^^xsd:dateTime ;
    dct:modified "2026-05-07T13:16:43.340725"^^xsd:dateTime ;
    dct:title "Monte Carlo Tree Search for Continuous and Stochastic Sequential Decision Making Problems" ;
    dcat:accessURL <https://theses.hal.science/tel-00927252> .

<https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> a foaf:Agent ;
    foaf:name "test_moissonnage_selune" .

<https://theses.hal.science/tel-00927252> a foaf:Document .