{"id":"https://openalex.org/W4416903727","doi":"https://doi.org/10.3390/info16121050","title":"Optimization of Multi-Intelligent Body Strategies for UAV Adversarial Tasks Based on MADDPG-SASP","display_name":"Optimization of Multi-Intelligent Body Strategies for UAV Adversarial Tasks Based on MADDPG-SASP","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W4416903727","doi":"https://doi.org/10.3390/info16121050"},"language":"en","primary_location":{"id":"doi:10.3390/info16121050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121050","pdf_url":null,"source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/info16121050","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhenfei Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenfei Xiao","raw_affiliation_strings":["School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China","institution_ids":["https://openalex.org/I4210119942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056233314","display_name":"Fuyong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111575","display_name":"Xinjiang Institute of Engineering","ror":"https://ror.org/01s5hh873","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210111575","https://openalex.org/I4210157944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuyong Liu","raw_affiliation_strings":["School of Information Science and Engineering, Xinjiang College of Science and Technology, Korla 841000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xinjiang College of Science and Technology, Korla 841000, China","institution_ids":["https://openalex.org/I4210111575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115596389","display_name":"Qian Wang","orcid":"https://orcid.org/0009-0006-7421-1451"},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qian Wang","raw_affiliation_strings":["School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China","institution_ids":["https://openalex.org/I4210119942"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5115596389"],"corresponding_institution_ids":["https://openalex.org/I4210119942"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.396,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87375923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"16","issue":"12","first_page":"1050","last_page":"1050"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.44269999861717224,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.44269999861717224,"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":0.1282999962568283,"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/T11133","display_name":"UAV Applications and Optimization","score":0.08309999853372574,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8095999956130981},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.7434999942779541},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.6951000094413757},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.5602999925613403},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5336999893188477},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4943000078201294},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4138000011444092},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.3294000029563904}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8095999956130981},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.7434999942779541},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6951000094413757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6110000014305115},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.5602999925613403},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5336999893188477},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4943000078201294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43630000948905945},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4138000011444092},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28519999980926514},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.267300009727478}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info16121050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121050","pdf_url":null,"source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4446b94ee5df4a3a886e282368e5ee2b","is_oa":true,"landing_page_url":"https://doaj.org/article/4446b94ee5df4a3a886e282368e5ee2b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 16, Iss 12, p 1050 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info16121050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121050","pdf_url":null,"source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"intelligent":[1],"multi-agent":[2,25,197],"systems,":[3],"particularly":[4],"in":[5,33,174,180,185],"drone":[6,204],"combat":[7,189],"scenarios,":[8],"the":[9,36,79,101,111,125,139,155,168,186,192,199,203],"challenges":[10],"posed":[11],"by":[12],"rapidly":[13],"changing":[14],"environments":[15],"and":[16,103,107,127,177,210],"incomplete":[17],"information":[18],"significantly":[19],"hinder":[20],"effective":[21],"strategy":[22,85,175],"optimization.":[23,86],"Traditional":[24],"reinforcement":[26],"learning":[27],"(MARL)":[28],"approaches":[29],"often":[30],"encounter":[31],"difficulties":[32],"adapting":[34],"to":[35,48,54,92,158],"dynamic":[37,182],"nature":[38],"of":[39,105,129,142],"adversarial":[40,121],"environments,":[41],"especially":[42],"when":[43,191],"enemy":[44,193],"strategies":[45,118],"are":[46],"subject":[47],"continuous":[49,120],"evolution,":[50],"complicating":[51],"agents\u2019":[52],"ability":[53],"respond":[55],"effectively.":[56],"To":[57],"address":[58],"these":[59],"challenges,":[60],"this":[61,145],"paper":[62],"introduces":[63],"a":[64,148,159,196],"novel":[65],"enhanced":[66],"MARL":[67],"framework,":[68],"MADDPG-SASP,":[69],"which":[70],"integrates":[71],"an":[72],"improved":[73],"self-attention":[74,88],"mechanism":[75,89,114],"with":[76,154],"self-play":[77],"within":[78],"MADDPG":[80,157],"algorithm,":[81],"thereby":[82,98,123],"facilitating":[83],"superior":[84],"The":[87],"empowers":[90],"agents":[91,143],"adaptively":[93],"extract":[94],"critical":[95],"environmental":[96],"features,":[97],"enhancing":[99],"both":[100],"speed":[102],"accuracy":[104],"perception":[106],"decision-making":[108],"processes.":[109],"Concurrently,":[110],"adaptive":[112],"self-battling":[113],"iteratively":[115],"refines":[116],"agent":[117,178,205],"through":[119,164],"interactions,":[122],"bolstering":[124],"stability":[126],"flexibility":[128],"their":[130],"responses.":[131],"Empirical":[132],"results":[133],"indicate":[134],"that":[135],"after":[136],"600":[137],"rounds,":[138],"win":[140,200],"rate":[141,201],"employing":[144],"framework":[146],"saw":[147],"substantial":[149],"increase,":[150],"rising":[151],"from":[152],"26.17%":[153],"original":[156],"perfect":[160],"100%.":[161,211],"Further":[162],"validation":[163],"comparative":[165],"experiments":[166],"underscores":[167],"method\u2019s":[169],"efficacy,":[170],"demonstrating":[171],"considerable":[172],"advantages":[173],"optimization":[176],"performance":[179],"complex,":[181],"environments.":[183],"Moreover,":[184],"Predator\u2013Prey":[187],"Scenario":[188],"environment,":[190],"side":[194,206],"employs":[195],"strategy,":[198],"for":[202],"can":[207],"reach":[208],"98.5%":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-12-02T00:00:00"}