{"id":"https://openalex.org/W4402351865","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651315","title":"Spatio-Temporal Graph Learning for Enhanced Agent Collaboration in Multi-Aircraft Combat","display_name":"Spatio-Temporal Graph Learning for Enhanced Agent Collaboration in Multi-Aircraft Combat","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351865","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651315"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651315","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5108982263","display_name":"Zhengchao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengchao Wang","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,Shenyang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101969200","display_name":"Cuiwei Liu","orcid":"https://orcid.org/0000-0003-4279-4841"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cuiwei Liu","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,Shenyang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100430457","display_name":"Yue Han","orcid":"https://orcid.org/0000-0002-7212-1122"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yue Han","raw_affiliation_strings":["SADRI Institute,Department of AI Center,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SADRI Institute,Department of AI Center,Shenyang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115590703","display_name":"Liang Chen","orcid":"https://orcid.org/0009-0005-2899-8997"},"institutions":[{"id":"https://openalex.org/I142078773","display_name":"Shenyang Institute of Automation","ror":"https://ror.org/00ft6nj33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I142078773","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Liang","raw_affiliation_strings":["Chinese Academy of Sciences,Shenyang Institute of Automation (SIA),Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Shenyang Institute of Automation (SIA),Shenyang,China","institution_ids":["https://openalex.org/I142078773","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083200173","display_name":"Huaijun Qiu","orcid":"https://orcid.org/0009-0007-2201-6264"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaijun Qiu","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,Shenyang,China","institution_ids":["https://openalex.org/I125904092"]}]}],"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":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T12158","display_name":"Guidance and Control Systems","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12158","display_name":"Guidance and Control Systems","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9975000023841858,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9878000020980835,"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/computer-science","display_name":"Computer science","score":0.6562950015068054},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48538196086883545},{"id":"https://openalex.org/keywords/multi-agent-system","display_name":"Multi-agent system","score":0.4490601718425751},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36305564641952515},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3371118903160095},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1715039610862732}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6562950015068054},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48538196086883545},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.4490601718425751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36305564641952515},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3371118903160095},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1715039610862732}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651315","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322539","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04"},{"id":"https://openalex.org/F4320336621","display_name":"Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2287267668","https://openalex.org/W2539402368","https://openalex.org/W2617547828","https://openalex.org/W2913756371","https://openalex.org/W2963762747","https://openalex.org/W2970066309","https://openalex.org/W2998367975","https://openalex.org/W3010424707","https://openalex.org/W3089592508","https://openalex.org/W3112673853","https://openalex.org/W3162388386","https://openalex.org/W4286748781","https://openalex.org/W4288091739","https://openalex.org/W4298857966","https://openalex.org/W4299802797","https://openalex.org/W4308613063","https://openalex.org/W4309483453","https://openalex.org/W4309761542","https://openalex.org/W4320015696","https://openalex.org/W4367627643","https://openalex.org/W4382202833","https://openalex.org/W4387394614","https://openalex.org/W6637967152","https://openalex.org/W6685444567","https://openalex.org/W6738796088","https://openalex.org/W6747473740","https://openalex.org/W6752380930","https://openalex.org/W6757797181","https://openalex.org/W6766805167","https://openalex.org/W6767098714","https://openalex.org/W6767327128","https://openalex.org/W6802002411","https://openalex.org/W6840380725","https://openalex.org/W6846544247"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"significant":[3],"progress":[4],"has":[5],"been":[6],"made":[7],"in":[8,19,41,124],"Multi-Agent":[9],"Deep":[10],"Reinforcement":[11],"Learning":[12,33],"(MADRL)":[13],"for":[14],"addressing":[15],"cooperative":[16,117,132],"decision-making":[17],"challenges":[18,40],"multi-aircraft":[20],"air":[21],"combat":[22,127],"tasks.":[23],"This":[24],"paper":[25],"introduces":[26],"a":[27,54,65,73,84,103],"novel":[28],"Spatio-Temporal":[29],"Relationship":[30],"Graph":[31,85],"Structure":[32],"method":[34],"(STRGSL),":[35],"aimed":[36],"at":[37],"overcoming":[38],"the":[39,43,110,116,136,146],"capturing":[42],"complex":[44],"and":[45,79,96,115,129],"dynamic":[46],"interactions":[47],"between":[48],"agents.":[49,120],"The":[50],"proposed":[51,137],"STRGSL":[52,89,101,138],"constructs":[53],"historical":[55,97],"behavior":[56],"graph":[57,68],"based":[58],"on":[59],"past":[60],"observations":[61],"as":[62,64],"well":[63],"real-time":[66],"interaction":[67],"from":[69],"current":[70,95],"observations,":[71],"providing":[72],"comprehensive":[74],"consideration":[75],"of":[76,112,119],"both":[77,109],"immediate":[78],"long-term":[80],"agent":[81,91],"relationships.":[82,98],"Leveraging":[83],"Neural":[86],"Network":[87],"(GNN),":[88],"generates":[90],"representations":[92],"that":[93,135],"fuse":[94],"By":[99],"integrating":[100],"into":[102],"MADRL":[104],"framework,":[105],"we":[106],"jointly":[107],"optimize":[108],"structure":[111],"relationship":[113],"graphs":[114],"policies":[118],"Experiments":[121],"carried":[122],"out":[123],"an":[125],"aircraft":[126],"scenario":[128],"two":[130],"multi-agent":[131],"scenarios":[133],"demonstrate":[134],"promotes":[139],"collaboration":[140],"among":[141],"multiple":[142],"agents,":[143],"thereby":[144],"enhancing":[145],"overall":[147],"performance":[148],"across":[149],"different":[150],"scenarios.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
