{"id":"https://openalex.org/W2165496254","doi":"https://doi.org/10.1109/ijcnn.2008.4634123","title":"A Q-Learning approach to developing an automated neural computer player for the board game of CLUE&lt;sup&gt;&amp;#x00AE;&lt;/sup&gt;","display_name":"A Q-Learning approach to developing an automated neural computer player for the board game of CLUE&lt;sup&gt;&amp;#x00AE;&lt;/sup&gt;","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2165496254","doi":"https://doi.org/10.1109/ijcnn.2008.4634123","mag":"2165496254"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4634123","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5013607775","display_name":"C. Cai","orcid":"https://orcid.org/0000-0003-3437-4820"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chenghui Cai","raw_affiliation_strings":["Mechanical Engineering, Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Mechanical Engineering, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101849469","display_name":"Silvio Ferrari","orcid":"https://orcid.org/0000-0002-7652-6311"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Silvia Ferrari","raw_affiliation_strings":["Faculty of Mechanical Engineering, Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Faculty of Mechanical Engineering, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013607775"],"corresponding_institution_ids":["https://openalex.org/I170897317"],"apc_list":null,"apc_paid":null,"fwci":2.8602,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91826588,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9887999892234802,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9887999892234802,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9872000217437744,"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":0.9858999848365784,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/treasure","display_name":"Treasure","score":0.7513850927352905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6628457307815552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6311450600624084},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5949351191520691},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4903383255004883},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.45480579137802124},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44680774211883545},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3901338577270508},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32838958501815796},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1399345099925995}],"concepts":[{"id":"https://openalex.org/C2776084483","wikidata":"https://www.wikidata.org/wiki/Q272937","display_name":"Treasure","level":2,"score":0.7513850927352905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6628457307815552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6311450600624084},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5949351191520691},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4903383255004883},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.45480579137802124},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44680774211883545},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3901338577270508},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32838958501815796},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1399345099925995},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2008.4634123","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W101508493","https://openalex.org/W1505812996","https://openalex.org/W1542941925","https://openalex.org/W1582102308","https://openalex.org/W1779246287","https://openalex.org/W1821294298","https://openalex.org/W1841450225","https://openalex.org/W2001863269","https://openalex.org/W2095953983","https://openalex.org/W2104883539","https://openalex.org/W2107649750","https://openalex.org/W2109234614","https://openalex.org/W2113168737","https://openalex.org/W2114368912","https://openalex.org/W2119567691","https://openalex.org/W2131600418","https://openalex.org/W2139385677","https://openalex.org/W2165891524","https://openalex.org/W2167549055","https://openalex.org/W2170588376","https://openalex.org/W2334782222","https://openalex.org/W2787259794","https://openalex.org/W3176183162","https://openalex.org/W4242811155","https://openalex.org/W4299670631","https://openalex.org/W6638759419"],"related_works":["https://openalex.org/W2492411721","https://openalex.org/W2223042459","https://openalex.org/W369913426","https://openalex.org/W2360017572","https://openalex.org/W4248194279","https://openalex.org/W1504426902","https://openalex.org/W2476851620","https://openalex.org/W4285698275","https://openalex.org/W378221013","https://openalex.org/W640718562"],"abstract_inverted_index":{"The":[0,41,75,197],"detective":[1],"board":[2,97],"game":[3,98],"of":[4,16,33,99,111,142,172],"CLUE":[5,100],"<sup":[6,101],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[7,102],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">reg</sup>":[8,103],"can":[9,122],"be":[10,123],"viewed":[11,44],"as":[12,45,86],"a":[13,23,112],"benchmark":[14],"example":[15],"the":[17,30,39,57,96,109,119,140,148,153,157,166,170],"treasure":[18,76],"hunt":[19,77],"problem,":[20],"in":[21,80,95],"which":[22,118,175],"sensor":[24,42],"path":[25,141],"is":[26,43,129,162,201],"planned":[27],"based":[28],"on":[29],"expected":[31],"value":[32,171],"information":[34,47,116],"gathered":[35],"from":[36,56,117],"targets":[37],"along":[38],"path.":[40],"an":[46,133,194],"gathering":[48],"agent":[49],"that":[50,138],"makes":[51,145],"imperfect":[52],"measurements":[53],"or":[54,65,73,211],"observations":[55],"targets,":[58],"and":[59,88,151,186],"uses":[60],"them":[61],"to":[62,114,131,164,203],"infer":[63],"one":[64],"more":[66],"hidden":[67,120,149],"variables":[68],"(such":[69],"as,":[70],"target":[71],"features":[72],"classification).":[74],"problem":[78],"arises":[79,94],"many":[81],"modern":[82],"surveillance":[83],"systems,":[84],"such":[85],"demining":[87],"reconnaissance":[89],"robotic":[90],"sensors.":[91],"Also,":[92],"it":[93],",":[104],"where":[105],"pawns":[106],"must":[107],"visit":[108],"rooms":[110],"mansion":[113],"gather":[115],"cards":[121],"inferred.":[124],"In":[125],"this":[126],"paper,":[127],"Q-learning":[128],"used":[130],"develop":[132],"automated":[134],"neural":[135,160],"computer":[136,199,206],"player":[137,200],"plans":[139],"its":[143],"pawn,":[144],"suggestions":[146],"about":[147],"cards,":[150],"infers":[152],"answer,":[154],"often":[155],"winning":[156],"game.":[158],"A":[159],"network":[161],"trained":[163],"approximate":[165],"decision-value":[167],"function":[168],"representing":[169],"information,":[173],"for":[174],"there":[176],"exists":[177],"no":[178],"general":[179],"closed-form":[180],"representation.":[181],"Bayesian":[182,209],"inference,":[183],"test":[184],"(suggestions),":[185],"action":[187],"(motion)":[188],"decision":[189],"making":[190],"are":[191],"unified":[192],"using":[193],"MDP":[195],"framework.":[196],"resulting":[198],"shown":[202],"outperform":[204],"other":[205],"players":[207],"implementing":[208],"networks,":[210],"constraint":[212],"satisfaction.":[213]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}