{"id":"https://openalex.org/W2885766801","doi":"https://doi.org/10.1109/cig.2018.8490368","title":"Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms","display_name":"Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2885766801","doi":"https://doi.org/10.1109/cig.2018.8490368","mag":"2885766801"},"language":"en","primary_location":{"id":"doi:10.1109/cig.2018.8490368","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2018.8490368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Conference on Computational Intelligence and Games (CIG)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084649185","display_name":"Maciej \u015awiechowski","orcid":"https://orcid.org/0000-0002-8941-3199"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Maciej Swiechowski","raw_affiliation_strings":["Silver Bullet Labs, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"Silver Bullet Labs, Warsaw, Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027080461","display_name":"Tomasz Tajmajer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tomasz Tajmajer","raw_affiliation_strings":["Silver Bullet Labs, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"Silver Bullet Labs, Warsaw, Poland","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006523416","display_name":"Andrzej Janusz","orcid":"https://orcid.org/0000-0002-9763-1399"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andrzej Janusz","raw_affiliation_strings":["eSensei, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"eSensei, Warsaw, Poland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084649185"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.8865,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.96064501,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.84612637758255},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.7663033604621887},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6700027585029602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6516627669334412},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6249757409095764},{"id":"https://openalex.org/keywords/video-game","display_name":"Video game","score":0.5931739211082458},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5433200001716614},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5225862264633179},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5178175568580627},{"id":"https://openalex.org/keywords/random-seed","display_name":"Random seed","score":0.47205930948257446},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.45295393466949463},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.42880022525787354},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4154955744743347},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3369501829147339},{"id":"https://openalex.org/keywords/random-number-generation","display_name":"Random number generation","score":0.0913105309009552},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.09047412872314453}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.84612637758255},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.7663033604621887},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6700027585029602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6516627669334412},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6249757409095764},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.5931739211082458},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5433200001716614},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5225862264633179},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5178175568580627},{"id":"https://openalex.org/C26263659","wikidata":"https://www.wikidata.org/wiki/Q1886131","display_name":"Random seed","level":3,"score":0.47205930948257446},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.45295393466949463},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.42880022525787354},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4154955744743347},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3369501829147339},{"id":"https://openalex.org/C201866948","wikidata":"https://www.wikidata.org/wiki/Q228206","display_name":"Random number generation","level":2,"score":0.0913105309009552},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.09047412872314453},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cig.2018.8490368","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2018.8490368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Conference on Computational Intelligence and Games (CIG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W16422172","https://openalex.org/W1628056908","https://openalex.org/W1646839507","https://openalex.org/W1891427008","https://openalex.org/W2056740053","https://openalex.org/W2058582651","https://openalex.org/W2073107347","https://openalex.org/W2075848246","https://openalex.org/W2077755260","https://openalex.org/W2099587183","https://openalex.org/W2102256448","https://openalex.org/W2113228754","https://openalex.org/W2117003664","https://openalex.org/W2126316555","https://openalex.org/W2131744502","https://openalex.org/W2134953825","https://openalex.org/W2153579005","https://openalex.org/W2170633032","https://openalex.org/W2257979135","https://openalex.org/W2574978968","https://openalex.org/W2589455135","https://openalex.org/W2590233375","https://openalex.org/W2594294527","https://openalex.org/W2757777359","https://openalex.org/W2766259847","https://openalex.org/W2767141304","https://openalex.org/W2772709170","https://openalex.org/W2884334892","https://openalex.org/W2963164996","https://openalex.org/W3141701062","https://openalex.org/W4294170691","https://openalex.org/W4321428174","https://openalex.org/W6636856942","https://openalex.org/W6639645198","https://openalex.org/W6675434749","https://openalex.org/W6677585109","https://openalex.org/W6679775712","https://openalex.org/W6682691769","https://openalex.org/W6734610637","https://openalex.org/W6745072467","https://openalex.org/W6746177919"],"related_works":["https://openalex.org/W2571592646","https://openalex.org/W4247855592","https://openalex.org/W2567165815","https://openalex.org/W2740304877","https://openalex.org/W2112583639","https://openalex.org/W2766259847","https://openalex.org/W2978000411","https://openalex.org/W2951716202","https://openalex.org/W4297907552","https://openalex.org/W2885766801"],"abstract_inverted_index":{"We":[0,34,54,71],"investigate":[1],"the":[2,9,18,40,63,85,99,110,115,119],"impact":[3],"of":[4,13,32,39,65,87],"supervised":[5],"prediction":[6],"models":[7],"on":[8],"strength":[10],"and":[11,51,81,113],"efficiency":[12],"artificial":[14],"agents":[15],"that":[16,42,73,93],"use":[17],"Monte-Carlo":[19],"Tree":[20],"Search":[21],"(MCTS)":[22],"algorithm":[23],"to":[24,61,98,107],"play":[25],"a":[26,96],"popular":[27],"video":[28],"game":[29,88,100],"Hearthstone:":[30],"Heroes":[31],"Warcraft.":[33],"overview":[35],"our":[36,66],"custom":[37],"implementation":[38],"MCTS":[41],"is":[43,105],"well-suited":[44],"for":[45,84],"games":[46],"with":[47],"partially":[48],"hidden":[49],"information":[50],"random":[52],"effects.":[53],"also":[55],"describe":[56],"experiments":[57],"which":[58],"we":[59,91],"designed":[60],"quantify":[62],"performance":[64],"Hearthstone":[67],"agent's":[68],"decision":[69],"making.":[70],"show":[72],"even":[74],"simple":[75],"neural":[76],"networks":[77],"can":[78],"be":[79],"trained":[80],"successfully":[82],"used":[83],"evaluation":[86],"states.":[89],"Moreover,":[90],"demonstrate":[92],"by":[94],"providing":[95],"guidance":[97],"state":[101],"search":[102],"heuristic,":[103],"it":[104],"possible":[106],"substantially":[108],"improve":[109],"win":[111],"rate,":[112],"at":[114],"same":[116],"time":[117],"reduce":[118],"required":[120],"computations.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}