{"id":"https://openalex.org/W2096188851","doi":"https://doi.org/10.1109/cig.2015.7317946","title":"Evaluating team behaviors constructed with human-guided machine learning","display_name":"Evaluating team behaviors constructed with human-guided machine learning","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2096188851","doi":"https://doi.org/10.1109/cig.2015.7317946","mag":"2096188851"},"language":"en","primary_location":{"id":"doi:10.1109/cig.2015.7317946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2015.7317946","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 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/A5108680366","display_name":"Igor V. Karpov","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Igor V. Karpov","raw_affiliation_strings":["Dept. of Computer Science, The University of Texas at Austin, Austin, TX, USA","Department of Computer Science, The University of Texas at Austin, 2317 Speedway, 2.302, Austin, TX 78712, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, The University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Austin, 2317 Speedway, 2.302, Austin, TX 78712, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111421004","display_name":"Leif Johnson","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leif M. Johnson","raw_affiliation_strings":["Dept. of Computer Science, The University of Texas at Austin, Austin, TX, USA","Department of Computer Science, The University of Texas at Austin, 2317 Speedway, 2.302, Austin, TX 78712, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, The University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Austin, 2317 Speedway, 2.302, Austin, TX 78712, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020441009","display_name":"Risto Miikkulainen","orcid":"https://orcid.org/0000-0002-0062-0037"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Risto Miikkulainen","raw_affiliation_strings":["Dept. of Computer Science, The University of Texas at Austin, Austin, TX, USA","Department of Computer Science, The University of Texas at Austin, 2317 Speedway, 2.302, Austin, TX 78712, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, The University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Austin, 2317 Speedway, 2.302, Austin, TX 78712, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5108680366"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":1.2943,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85800452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"292","last_page":"298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.998199999332428,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.998199999332428,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9846000075340271,"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/computer-science","display_name":"Computer science","score":0.6900953054428101},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4746192991733551},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.43557628989219666},{"id":"https://openalex.org/keywords/human\u2013machine-system","display_name":"Human\u2013machine system","score":0.43291518092155457},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41443198919296265}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6900953054428101},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4746192991733551},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.43557628989219666},{"id":"https://openalex.org/C146047270","wikidata":"https://www.wikidata.org/wiki/Q469666","display_name":"Human\u2013machine system","level":2,"score":0.43291518092155457},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41443198919296265}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cig.2015.7317946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2015.7317946","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W102217165","https://openalex.org/W1602676878","https://openalex.org/W1674110665","https://openalex.org/W2012354607","https://openalex.org/W2053153219","https://openalex.org/W2096645045","https://openalex.org/W2106486115","https://openalex.org/W2111935653","https://openalex.org/W2121462546","https://openalex.org/W2140685838","https://openalex.org/W2148317584","https://openalex.org/W4205722997","https://openalex.org/W4231663993","https://openalex.org/W6604107930","https://openalex.org/W6637442801"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W3046775127","https://openalex.org/W4205958290","https://openalex.org/W3107474891","https://openalex.org/W3209574120","https://openalex.org/W3170094116"],"abstract_inverted_index":{"Machine":[0],"learning":[1,42,130],"games":[2,142],"such":[3,9,39],"as":[4,10,12],"NERO":[5],"incorporate":[6],"adaptive":[7],"methods":[8,43,131],"neuroevolution":[11],"an":[13],"integral":[14],"part":[15],"of":[16,26,48,66,89],"the":[17,21,45,62,90,94,133,149],"gameplay":[18],"by":[19],"allowing":[20],"player":[22],"to":[23,82,124,140],"train":[24],"teams":[25,47,91],"autonomous":[27],"agents":[28],"for":[29,93],"effective":[30],"behavior":[31],"in":[32,148],"challenging":[33,53],"open-ended":[34],"tasks.":[35],"However,":[36],"rigorously":[37],"evaluating":[38],"human-guided":[40,128],"machine":[41,129],"and":[44,54,64,79,105,108,112,117,126,132,143],"resulting":[46,134],"agent":[49,77],"policies":[50],"can":[51],"be":[52,83],"is":[55],"thus":[56],"rarely":[57],"done.":[58],"This":[59],"paper":[60],"presents":[61],"results":[63],"analysis":[65,88,118],"a":[67,97,121],"large":[68],"scale":[69],"online":[70],"tournament":[71,95,116],"between":[72],"participants":[73],"who":[74],"evolved":[75],"team":[76,136],"behaviors":[78],"submitted":[80,92],"them":[81],"compared":[84],"with":[85],"others.":[86],"An":[87],"indicates":[96],"complex,":[98],"non-transitive":[99],"fitness":[100],"landscape,":[101],"multiple":[102],"successful":[103],"strategies":[104],"training":[106],"approaches,":[107],"performance":[109],"above":[110],"hand-constructed":[111],"random":[113],"baselines.":[114],"The":[115],"presented":[119],"provide":[120],"practical":[122],"way":[123],"study":[125],"improve":[127],"NPC":[135],"behaviors,":[137],"potentially":[138],"leading":[139],"better":[141,144],"game":[145],"design":[146],"tools":[147],"future.":[150]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
