{"id":"https://openalex.org/W7161998319","doi":"https://doi.org/10.48550/arxiv.2605.20911","title":"For How Long Should We Be Punching? Learning Action Duration in Fighting Games","display_name":"For How Long Should We Be Punching? Learning Action Duration in Fighting Games","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161998319","doi":"https://doi.org/10.48550/arxiv.2605.20911"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20911","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20911","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.20911","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5131539764","display_name":"Hoang Hai Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Hoang Hai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136667789","display_name":"Kurt Driessens","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Driessens, Kurt","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125606068","display_name":"Dennis J.N.J. Soemers","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Soemers, Dennis J. N. J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.704800009727478,"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":0.704800009727478,"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":0.1574999988079071,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.008700000122189522,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/frame","display_name":"Frame (networking)","score":0.6751999855041504},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.675000011920929},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.67330002784729},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.613099992275238},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.36809998750686646},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.3280999958515167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7081999778747559},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6751999855041504},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.675000011920929},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.67330002784729},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.613099992275238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5113000273704529},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.37610000371932983},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3540000021457672},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.3278000056743622},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.32269999384880066},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C5065155","wikidata":"https://www.wikidata.org/wiki/Q1185775","display_name":"Frame problem","level":2,"score":0.2565000057220459}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20911","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20911","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.20911","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20911","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8162233233451843}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Fighting":[0],"games":[1],"such":[2],"as":[3],"Street":[4],"Fighter":[5],"II":[6],"present":[7],"unique":[8],"challenges":[9],"to":[10,16,28,53,68,96,103,120,148,207,225],"reinforcement":[11],"learning":[12],"(RL)":[13],"agents":[14,25,136,190],"due":[15],"their":[17,150],"fast-paced,":[18],"real-time":[19],"nature.":[20],"In":[21,185],"most":[22,186],"RL":[23],"frameworks,":[24],"are":[26,65],"hard-coded":[27],"make":[29],"decisions":[30],"at":[31],"a":[32],"fixed":[33,73,169],"interval,":[34],"typically":[35],"every":[36,39,59],"frame":[37,60,145,170,196],"or":[38],"N":[40],"frames.":[41],"Although":[42],"this":[43,128],"design":[44],"ensures":[45],"timely":[46],"responses,":[47],"it":[48,205],"restricts":[49],"the":[50,89,113,124,131,165,212,221],"agent's":[51],"ability":[52],"adjust":[54],"its":[55,118,183],"reaction":[56],"timing.":[57],"Acting":[58],"grants":[61],"frame-perfect":[62],"reflexes,":[63],"which":[64,88,220],"unrealistic":[66],"compared":[67],"human":[69],"players,":[70],"whereas":[71],"longer":[72],"intervals":[74],"reduce":[75],"computational":[76],"cost":[77],"but":[78,98,177],"hinder":[79],"responsiveness.":[80],"We":[81,126],"consider":[82],"an":[83],"alternative":[84],"decision-making":[85],"framework":[86],"in":[87,123],"agent":[90,114],"learns":[91],"not":[92,179],"only":[93],"what":[94],"action":[95,110,175,214],"take":[97],"also":[99],"for":[100],"how":[101],"long":[102],"execute":[104],"it.":[105],"By":[106],"jointly":[107],"predicting":[108],"both":[109],"and":[111,155,172,218],"duration,":[112],"can":[115,163],"dynamically":[116],"adapt":[117],"responsiveness":[119],"different":[121,144],"situations":[122],"game.":[125],"implement":[127],"method":[129],"using":[130],"open-source":[132],"FightLadder":[133],"environment":[134],"with":[135,193],"trained":[137],"against":[138],"scripted":[139,222],"built-in":[140],"bots,":[141],"systematically":[142],"testing":[143],"skip":[146,197],"configurations":[147],"analyze":[149],"influence":[151],"on":[152,182],"performance,":[153],"responsiveness,":[154],"learned":[156,161],"behavior.":[157],"Experiments":[158],"show":[159],"that":[160],"timing":[162],"match":[164],"performance":[166],"of":[167],"well-chosen":[168],"skips":[171],"encourages":[173],"repeatable":[174],"patterns,":[176],"does":[178],"ensure":[180],"robustness":[181],"own.":[184],"cases,":[187],"we":[188],"see":[189],"performing":[191],"best":[192],"consistently":[194],"high":[195],"values":[198],"(i.e.,":[199],"low":[200],"responsiveness).":[201],"This":[202],"strategy":[203],"makes":[204],"easier":[206],"learn":[208],"exploitative":[209],"strategies":[210],"where":[211],"same":[213],"is":[215],"repeated":[216],"over":[217],"over,":[219],"bots":[223],"appear":[224],"be":[226],"susceptible":[227],"to.":[228]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-22T00:00:00"}
