{"id":"https://openalex.org/W3186144828","doi":"https://doi.org/10.1145/3474658","title":"Predicting Game Difficulty and Engagement Using AI Players","display_name":"Predicting Game Difficulty and Engagement Using AI Players","publication_year":2021,"publication_date":"2021-10-05","ids":{"openalex":"https://openalex.org/W3186144828","doi":"https://doi.org/10.1145/3474658","mag":"3186144828"},"language":"en","primary_location":{"id":"doi:10.1145/3474658","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474658","pdf_url":null,"source":{"id":"https://openalex.org/S4210183893","display_name":"Proceedings of the ACM on Human-Computer Interaction","issn_l":"2573-0142","issn":["2573-0142"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Human-Computer Interaction","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2107.12061","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shaghayegh Roohi","orcid":null},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Shaghayegh Roohi","raw_affiliation_strings":["Aalto University, Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Aalto University, Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Christian Guckelsberger","orcid":null},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Christian Guckelsberger","raw_affiliation_strings":["Aalto University, Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Aalto University, Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Asko Relas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Asko Relas","raw_affiliation_strings":["Rovio Entertainment, Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Rovio Entertainment, Espoo, Finland","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Henri Heiskanen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Henri Heiskanen","raw_affiliation_strings":["Rovio Entertainment, Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Rovio Entertainment, Espoo, Finland","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jari Takatalo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jari Takatalo","raw_affiliation_strings":["Rovio Entertainment, Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Rovio Entertainment, Espoo, Finland","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Perttu H\u00e4m\u00e4l\u00e4inen","orcid":null},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Perttu H\u00e4m\u00e4l\u00e4inen","raw_affiliation_strings":["Aalto University, Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Aalto University, Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9927081"],"apc_list":null,"apc_paid":null,"fwci":1.5395,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8603929,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"5","issue":"CHI PLAY","first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9086999893188477,"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":0.9086999893188477,"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":0.0203000009059906,"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":0.007899999618530273,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6481999754905701},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.6211000084877014},{"id":"https://openalex.org/keywords/operationalization","display_name":"Operationalization","score":0.5612999796867371},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.49869999289512634},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.43720000982284546},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.43549999594688416},{"id":"https://openalex.org/keywords/video-game","display_name":"Video game","score":0.3174000084400177}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6796000003814697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6769999861717224},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6481999754905701},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.6211000084877014},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6062999963760376},{"id":"https://openalex.org/C9354725","wikidata":"https://www.wikidata.org/wiki/Q286017","display_name":"Operationalization","level":2,"score":0.5612999796867371},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43720000982284546},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.43549999594688416},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3474658","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474658","pdf_url":null,"source":{"id":"https://openalex.org/S4210183893","display_name":"Proceedings of the ACM on Human-Computer Interaction","issn_l":"2573-0142","issn":["2573-0142"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Human-Computer Interaction","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2107.12061","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.12061","pdf_url":"https://arxiv.org/pdf/2107.12061","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:aaltodoc.aalto.fi:123456789/111259","is_oa":true,"landing_page_url":"https://research.aalto.fi/en/publications/e1c78f71-0399-4cc7-bc04-e1e9fd0d18d6","pdf_url":"https://research.aalto.fi/files/76132762/SCI_Roohi_Predicting_Game_Difficulty_and_Engagement_Using_AI_Players.pdf","source":{"id":"https://openalex.org/S4306401663","display_name":"Aaltodoc (Aalto University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I9927081","host_organization_name":"Aalto University","host_organization_lineage":["https://openalex.org/I9927081"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"acceptedVersion"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2107.12061","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.12061","pdf_url":"https://arxiv.org/pdf/2107.12061","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2686771648","display_name":null,"funder_award_id":"(Finnish Center for Artificial Intelligence)","funder_id":"https://openalex.org/F4320321108","funder_display_name":"Academy of Finland"}],"funders":[{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"},{"id":"https://openalex.org/F4320332050","display_name":"Finnish Center for Artificial Intelligence","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1625390266","https://openalex.org/W1892018222","https://openalex.org/W1924976642","https://openalex.org/W2036493203","https://openalex.org/W2040820483","https://openalex.org/W2045712037","https://openalex.org/W2069897595","https://openalex.org/W2077434199","https://openalex.org/W2102669142","https://openalex.org/W2108631245","https://openalex.org/W2108682032","https://openalex.org/W2113410615","https://openalex.org/W2121813011","https://openalex.org/W2126316555","https://openalex.org/W2144230296","https://openalex.org/W2145339207","https://openalex.org/W2170899200","https://openalex.org/W2257979135","https://openalex.org/W2334782222","https://openalex.org/W2606862087","https://openalex.org/W2611228102","https://openalex.org/W2761234549","https://openalex.org/W2765692642","https://openalex.org/W2766324411","https://openalex.org/W2792893218","https://openalex.org/W2795733309","https://openalex.org/W2803408358","https://openalex.org/W2897406577","https://openalex.org/W2909134974","https://openalex.org/W2955799434","https://openalex.org/W2963523627","https://openalex.org/W2974997023","https://openalex.org/W2975007272","https://openalex.org/W2980810656","https://openalex.org/W2996368260","https://openalex.org/W3011388507","https://openalex.org/W3023258177","https://openalex.org/W3030715443","https://openalex.org/W3031421239","https://openalex.org/W3081860130","https://openalex.org/W3093544082","https://openalex.org/W3093621925","https://openalex.org/W3093787047","https://openalex.org/W3094248940","https://openalex.org/W3094597259","https://openalex.org/W3094617642","https://openalex.org/W3096715124","https://openalex.org/W4206908526","https://openalex.org/W4246277771","https://openalex.org/W6669402789"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,132],"novel":[4],"approach":[5,47],"to":[6,130],"automated":[7,116],"playtesting":[8,117],"for":[9,64],"the":[10,69,85,93,97,107],"prediction":[11,94],"of":[12,134],"human":[13,82],"player":[14,35,113],"behavior":[15],"and":[16,34,41,96,103,123],"experience.":[17],"We":[18,44,57,110],"have":[19],"previously":[20],"demonstrated":[21],"that":[22,71,112],"Deep":[23],"Reinforcement":[24],"Learning":[25],"(DRL)":[26],"game-playing":[27],"agents":[28],"can":[29,77,118,127],"predict":[30],"both":[31,101],"game":[32],"difficulty":[33],"engagement,":[36],"operationalized":[37],"as":[38],"average":[39,87],"pass":[40],"churn":[42],"rates.":[43],"improve":[45,92],"this":[46],"by":[48],"enhancing":[49],"DRL":[50,102,122],"with":[51,81],"Monte":[52],"Carlo":[53],"Tree":[54],"Search":[55],"(MCTS).":[56],"also":[58],"motivate":[59],"an":[60,72],"enhanced":[61],"selection":[62],"strategy":[63],"predictor":[65],"features,":[66],"based":[67],"on":[68,148],"observation":[70],"AI":[73,137,141],"agent's":[74,86],"best-case":[75],"performance":[76],"yield":[78,145],"stronger":[79],"correlations":[80],"data":[83],"than":[84],"performance.":[88],"Both":[89],"additions":[90],"consistently":[91],"accuracy,":[95],"DRL-enhanced":[98],"MCTS":[99,105],"outperforms":[100],"vanilla":[104],"in":[106],"hardest":[108],"levels.":[109],"conclude":[111],"modelling":[114],"via":[115],"benefit":[119],"from":[120],"combining":[121],"MCTS.":[124],"Moreover,":[125],"it":[126],"be":[128],"worthwhile":[129],"investigate":[131],"subset":[133],"repeated":[135],"best":[136],"agent":[138],"runs,":[139],"if":[140],"gameplay":[142],"does":[143],"not":[144],"good":[146],"predictions":[147],"average.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":6}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2021-08-02T00:00:00"}
