{"id":"https://openalex.org/W3207318282","doi":"https://doi.org/10.48550/arxiv.2110.04507","title":"TiKick: Towards Playing Multi-agent Football Full Games from Single-agent Demonstrations","display_name":"TiKick: Towards Playing Multi-agent Football Full Games from Single-agent Demonstrations","publication_year":2021,"publication_date":"2021-10-09","ids":{"openalex":"https://openalex.org/W3207318282","doi":"https://doi.org/10.48550/arxiv.2110.04507","mag":"3207318282"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2110.04507","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.04507","pdf_url":"https://arxiv.org/pdf/2110.04507","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2110.04507","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101984824","display_name":"Shiyu Huang","orcid":"https://orcid.org/0000-0003-0500-0141","observed_orcids":["https://orcid.org/0000-0003-0500-0141"]},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huang, Shiyu","raw_affiliation_strings":["Tsinghua University Beijing , China","Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University Beijing , China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044234682","display_name":"Wenze Chen","orcid":"https://orcid.org/0000-0002-7232-0148","observed_orcids":["https://orcid.org/0000-0002-7232-0148"]},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen, Wenze","raw_affiliation_strings":["Tsinghua University Beijing , China","Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University Beijing , China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100710449","display_name":"Longfei Zhang","orcid":"https://orcid.org/0000-0002-2571-4953","observed_orcids":["https://orcid.org/0000-0002-2571-4953"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Longfei","raw_affiliation_strings":["National University of Defense Technology Changsha , China","National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology Changsha , China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xu, Shizhen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu, Shizhen","raw_affiliation_strings":["RealAI Beijing , China","TENCENT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RealAI Beijing , China","institution_ids":[]},{"raw_affiliation_string":"TENCENT","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422860","display_name":"Ziyang Li","orcid":"https://orcid.org/0000-0002-6064-8875","observed_orcids":["https://orcid.org/0000-0002-6064-8875"]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li, Ziyang","raw_affiliation_strings":["Tencent AI Lab Shenzhen , China","TENCENT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab Shenzhen , China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"TENCENT","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhu, Fengming","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhu, Fengming","raw_affiliation_strings":["Tencent AI Lab Shenzhen , China","TENCENT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab Shenzhen , China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"TENCENT","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073681676","display_name":"Deheng Ye","orcid":"https://orcid.org/0000-0002-1754-1837","observed_orcids":["https://orcid.org/0000-0002-1754-1837"]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye, Deheng","raw_affiliation_strings":["Tencent AI Lab Shenzhen , China","Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab Shenzhen , China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044300905","display_name":"Ting Chen","orcid":"https://orcid.org/0000-0002-7515-6128","observed_orcids":["https://orcid.org/0000-0002-7515-6128"]},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen, Ting","raw_affiliation_strings":["Tsinghua University Beijing , China","Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University Beijing , China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100606995","display_name":"Jun Zhu","orcid":"https://orcid.org/0000-0002-6254-2388","observed_orcids":["https://orcid.org/0000-0002-6254-2388"]},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhu, Jun","raw_affiliation_strings":["Tsinghua University Beijing , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University Beijing , China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":32,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9976000189781189,"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":0.9976000189781189,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.002099999925121665,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0,"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/multi-agent-reinforcement-learning","display_name":"multi-agent reinforcement learning","score":0.8199999928474426},{"id":"https://openalex.org/keywords/football-video-games","display_name":"football video games","score":0.7129999995231628},{"id":"https://openalex.org/keywords/google-research-football","display_name":"Google Research Football","score":0.9900000095367432},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"distributed learning","score":0.800000011920929},{"id":"https://openalex.org/keywords/offline-learning","display_name":"offline learning","score":0.7409999966621399},{"id":"https://openalex.org/keywords/sparse-rewards","display_name":"sparse rewards","score":0.5509999990463257},{"id":"https://openalex.org/keywords/self-play","display_name":"self-play","score":0.5},{"id":"https://openalex.org/keywords/multiagent-coordination","display_name":"multi-agent coordination","score":0.5979999899864197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7881956100463867},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.7571010589599609},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.748365044593811},{"id":"https://openalex.org/C2778444522","wikidata":"https://www.wikidata.org/wiki/Q1081491","display_name":"Football","level":2,"score":0.630332350730896},{"id":"https://openalex.org/C207456731","wikidata":"https://www.wikidata.org/wiki/Q660818","display_name":"League","level":2,"score":0.5695613622665405},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.5339010953903198},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5277291536331177},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5232516527175903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49321407079696655},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.42984676361083984},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3604505658149719},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3542343080043793},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19922900199890137},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1084410548210144},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0718468427658081},{"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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2110.04507","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.04507","pdf_url":"https://arxiv.org/pdf/2110.04507","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"doi:10.48550/arxiv.2110.04507","doi":"https://doi.org/10.48550/arxiv.2110.04507","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2110.04507","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2110.04507","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.04507","pdf_url":"https://arxiv.org/pdf/2110.04507","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3207318282.pdf","grobid_xml":"https://content.openalex.org/works/W3207318282.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1191599655","https://openalex.org/W1522301498","https://openalex.org/W1757796397","https://openalex.org/W2034587361","https://openalex.org/W2125930537","https://openalex.org/W2153975459","https://openalex.org/W2257979135","https://openalex.org/W2434014514","https://openalex.org/W2623431351","https://openalex.org/W2747213132","https://openalex.org/W2803616302","https://openalex.org/W2804380964","https://openalex.org/W2883057932","https://openalex.org/W2891076394","https://openalex.org/W2911616846","https://openalex.org/W2950635152","https://openalex.org/W2963243556","https://openalex.org/W2963351448","https://openalex.org/W2963704132","https://openalex.org/W2964121744","https://openalex.org/W2970514967","https://openalex.org/W2978455699","https://openalex.org/W2981141126","https://openalex.org/W2982316857","https://openalex.org/W2991355586","https://openalex.org/W2996037775","https://openalex.org/W2996145485","https://openalex.org/W3016525976","https://openalex.org/W3028766998","https://openalex.org/W3033324992","https://openalex.org/W3034607397","https://openalex.org/W3093287223","https://openalex.org/W3096726323","https://openalex.org/W3106426955","https://openalex.org/W3113190209","https://openalex.org/W3134226813","https://openalex.org/W3164631379","https://openalex.org/W3169363132","https://openalex.org/W3170473100","https://openalex.org/W3185826690","https://openalex.org/W3212314511","https://openalex.org/W7133210602","https://openalex.org/W7133226216"],"related_works":["https://openalex.org/W7124302995","https://openalex.org/W7093708511","https://openalex.org/W7171667975","https://openalex.org/W4390814006","https://openalex.org/W4360825542","https://openalex.org/W4382618452","https://openalex.org/W7203530626","https://openalex.org/W7045858829","https://openalex.org/W4392029873","https://openalex.org/W7036107916"],"abstract_inverted_index":{"Deep":[0],"reinforcement":[1],"learning":[2,96],"(DRL)":[3],"has":[4],"achieved":[5],"super-human":[6],"performance":[7],"on":[8,148,176],"complex":[9],"video":[10,44],"games":[11],"(e.g.,":[12],"StarCraft":[13],"II":[14],"and":[15,54,98,170],"Dota":[16],"II).":[17],"However,":[18],"current":[19],"DRL":[20],"systems":[21],"still":[22],"suffer":[23],"from":[24,79,88,108],"challenges":[25],"of":[26,82,116,165],"multi-agent":[27,106,131,168],"coordination,":[28],"sparse":[29],"rewards,":[30],"stochastic":[31],"environments,":[32],"etc.":[33],"In":[34,69],"seeking":[35],"to":[36,64,102],"address":[37],"these":[38],"challenges,":[39],"we":[40,72],"employ":[41],"a":[42,75,94,104,143],"football":[43],"game,":[45,136],"e.g.,":[46],"Google":[47,132],"Research":[48,133],"Football":[49,134],"(GRF),":[50],"as":[51,62],"our":[52,117,157,171],"testbed":[53],"develop":[55],"an":[56],"end-to-end":[57],"learning-based":[58,123],"AI":[59,107,124],"system":[60,97,125],"(denoted":[61],"TiKick)":[63],"complete":[65],"this":[66,70],"challenging":[67],"task.":[68],"work,":[71],"first":[73,122],"generated":[74],"large":[76],"replay":[77],"dataset":[78],"the":[80,109,114,121,130,162,166],"self-playing":[81],"single-agent":[83,111],"experts,":[84],"which":[85],"are":[86],"obtained":[87],"league":[89],"training.":[90],"We":[91],"then":[92],"developed":[93],"distributed":[95],"new":[99],"offline":[100],"algorithms":[101],"learn":[103],"powerful":[105],"fixed":[110],"dataset.":[112],"To":[113],"best":[115],"knowledge,":[118],"Tikick":[119],"is":[120],"that":[126,156],"can":[127,160],"take":[128],"over":[129],"full":[135],"while":[137],"previous":[138],"work":[139],"could":[140],"either":[141],"control":[142],"single":[144],"agent":[145],"or":[146],"experiment":[147],"toy":[149],"academic":[150,178],"scenarios.":[151,179],"Extensive":[152],"experiments":[153],"further":[154],"show":[155],"pre-trained":[158],"model":[159],"accelerate":[161],"training":[163],"process":[164],"modern":[167],"algorithm":[169],"method":[172],"achieves":[173],"state-of-the-art":[174],"performances":[175],"various":[177]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2021-10-25T00:00:00"}