{"id":"https://openalex.org/W2896445362","doi":"https://doi.org/10.1109/cig.2018.8490411","title":"Forward Model Approximation for General Video Game Learning","display_name":"Forward Model Approximation for General Video Game Learning","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2896445362","doi":"https://doi.org/10.1109/cig.2018.8490411","mag":"2896445362"},"language":"en","primary_location":{"id":"doi:10.1109/cig.2018.8490411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2018.8490411","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/A5006873204","display_name":"Alexander Dockhorn","orcid":"https://orcid.org/0000-0001-8711-7428"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke University Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alexander Dockhorn","raw_affiliation_strings":["Otto von Guericke University, Magdeburg, Germany"],"affiliations":[{"raw_affiliation_string":"Otto von Guericke University, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052120977","display_name":"Daan Apeldoorn","orcid":"https://orcid.org/0000-0001-5170-5893"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daan Apeldoorn","raw_affiliation_strings":["Z Quadrat GmbH, Mainz, Germany"],"affiliations":[{"raw_affiliation_string":"Z Quadrat GmbH, Mainz, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006873204"],"corresponding_institution_ids":["https://openalex.org/I95793202"],"apc_list":null,"apc_paid":null,"fwci":2.6061,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.92093751,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"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":0.9997000098228455,"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":0.9997000098228455,"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":0.9930999875068665,"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/T11197","display_name":"Digital Games and Media","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7816988229751587},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.7582650780677795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6105988025665283},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5890881419181824},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5539358258247375},{"id":"https://openalex.org/keywords/video-game","display_name":"Video game","score":0.5483825206756592},{"id":"https://openalex.org/keywords/game-tree","display_name":"Game tree","score":0.49950599670410156},{"id":"https://openalex.org/keywords/sequential-game","display_name":"Sequential game","score":0.47346559166908264},{"id":"https://openalex.org/keywords/game-mechanics","display_name":"Game mechanics","score":0.4525229334831238},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4466245770454407},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.42852532863616943},{"id":"https://openalex.org/keywords/game-theory","display_name":"Game theory","score":0.40358591079711914},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.26043152809143066},{"id":"https://openalex.org/keywords/mathematical-economics","display_name":"Mathematical economics","score":0.11157301068305969},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10449159145355225},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.08653289079666138}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7816988229751587},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.7582650780677795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6105988025665283},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5890881419181824},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5539358258247375},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.5483825206756592},{"id":"https://openalex.org/C95815963","wikidata":"https://www.wikidata.org/wiki/Q1377033","display_name":"Game tree","level":4,"score":0.49950599670410156},{"id":"https://openalex.org/C73795354","wikidata":"https://www.wikidata.org/wiki/Q287618","display_name":"Sequential game","level":3,"score":0.47346559166908264},{"id":"https://openalex.org/C170828538","wikidata":"https://www.wikidata.org/wiki/Q1751513","display_name":"Game mechanics","level":2,"score":0.4525229334831238},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4466245770454407},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.42852532863616943},{"id":"https://openalex.org/C177142836","wikidata":"https://www.wikidata.org/wiki/Q44455","display_name":"Game theory","level":2,"score":0.40358591079711914},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.26043152809143066},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.11157301068305969},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10449159145355225},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.08653289079666138},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cig.2018.8490411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2018.8490411","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2025400977","https://openalex.org/W2028208918","https://openalex.org/W2099587183","https://openalex.org/W2269274350","https://openalex.org/W2569196563","https://openalex.org/W2590549092","https://openalex.org/W2602193277","https://openalex.org/W2612446991","https://openalex.org/W2728509558","https://openalex.org/W2765689447","https://openalex.org/W2785767082","https://openalex.org/W2785943113","https://openalex.org/W2803218890","https://openalex.org/W2912429934","https://openalex.org/W2962731213","https://openalex.org/W4295231058","https://openalex.org/W6675434749","https://openalex.org/W6736273821","https://openalex.org/W6737770317","https://openalex.org/W6740517196","https://openalex.org/W6747825032","https://openalex.org/W6751741166","https://openalex.org/W6759062285"],"related_works":["https://openalex.org/W4383535542","https://openalex.org/W3193783858","https://openalex.org/W4383560925","https://openalex.org/W1973194029","https://openalex.org/W2523674799","https://openalex.org/W4287370909","https://openalex.org/W2252918381","https://openalex.org/W2914188613","https://openalex.org/W3121173017","https://openalex.org/W332195970"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,9,27,69,80,138,155,174],"novel":[4,81],"learning":[5,49,129],"agent":[6,16,72,133],"model":[7,23,152],"for":[8,99],"General":[10,164],"Video":[11,165],"Game":[12,166],"Playing":[13],"agent.":[14],"Our":[15],"learns":[17,43],"an":[18],"approximation":[19,153],"of":[20,60,68,158,163],"the":[21,44,71,100,120,128,161,185],"forward":[22,151],"from":[24,124],"repeatedly":[25],"playing":[26],"game":[28,45,106],"and":[29,51,93],"subsequently":[30],"adapting":[31],"its":[32,77,146],"behavior":[33],"to":[34,75,114,172,179],"previously":[35],"unseen":[36],"levels.":[37],"To":[38],"achieve":[39],"this,":[40],"it":[41,97],"first":[42],"mechanics":[46],"through":[47],"machine":[48],"techniques":[50],"then":[52],"extracts":[53],"rule-based":[54,122],"symbolic":[55],"knowledge":[56,78,123],"on":[57],"different":[58],"levels":[59,67],"abstraction.":[61],"When":[62],"being":[63,143],"confronted":[64],"with":[65],"new":[66,156],"game,":[70],"is":[73],"able":[74],"revise":[76],"by":[79,137],"belief":[82],"revision":[83],"approach.":[84],"Using":[85],"methods":[86],"such":[87],"as":[88],"Monte":[89],"Carlo":[90],"Tree":[91],"Search":[92],"Breadth":[94],"First":[95],"Search,":[96],"searches":[98],"best":[101],"possible":[102,112],"action":[103],"using":[104,119],"simulated":[105],"episodes.":[107],"Those":[108],"simulations":[109],"are":[110],"only":[111],"due":[113],"reasoning":[115],"about":[116],"future":[117],"states":[118],"extracted":[121],"random":[125],"episodes":[126],"during":[127],"phase.":[130],"The":[131,149],"developed":[132],"outperforms":[134],"previous":[135],"agents":[136],"large":[139],"margin,":[140],"while":[141],"still":[142],"limited":[144],"in":[145,160,183],"prediction":[147],"capabilities.":[148],"proposed":[150],"opens":[154],"class":[157],"solutions":[159],"context":[162],"Playing,":[167],"which":[168],"do":[169],"not":[170],"try":[171,178],"learn":[173],"value":[175],"function,":[176],"but":[177],"increase":[180],"their":[181],"accuracy":[182],"modelling":[184],"game.":[186]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}