{"id":"https://openalex.org/W4402352954","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651091","title":"Improved Communication and Collision-Avoidance in Dynamic Multi-Agent Path Finding","display_name":"Improved Communication and Collision-Avoidance in Dynamic Multi-Agent Path Finding","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352954","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651091"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651091","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/A5107748200","display_name":"Jing Xie","orcid":null},"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":"Jing Xie","raw_affiliation_strings":["National Innovation Institute of Defense Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Innovation Institute of Defense Technology,Beijing,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108625236","display_name":"Yongjun Zhang","orcid":"https://orcid.org/0000-0001-9845-4251"},"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":"Yongjun Zhang","raw_affiliation_strings":["National Innovation Institute of Defense Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Innovation Institute of Defense Technology,Beijing,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102846370","display_name":"Qianying Ouyang","orcid":"https://orcid.org/0009-0009-0027-7564"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qianying Ouyang","raw_affiliation_strings":["Intelligent Game and Decision Lab,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Game and Decision Lab,Beijing,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012369858","display_name":"Huanhuan Yang","orcid":"https://orcid.org/0000-0002-9632-2543"},"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":"Huanhuan Yang","raw_affiliation_strings":["National University of Defense Technology,College of Computer,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Computer,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605495","display_name":"Fang Dong","orcid":"https://orcid.org/0000-0001-6770-326X"},"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":"Fang Dong","raw_affiliation_strings":["National University of Defense Technology,College of Computer,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Computer,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019758816","display_name":"Dianxi Shi","orcid":"https://orcid.org/0000-0002-8112-371X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dianxi Shi","raw_affiliation_strings":["Intelligent Game and Decision Lab,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Game and Decision Lab,Beijing,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100707142","display_name":"Songchang Jin","orcid":"https://orcid.org/0000-0002-5959-0768"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Songchang Jin","raw_affiliation_strings":["Intelligent Game and Decision Lab,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Game and Decision Lab,Beijing,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998999834060669,"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"}},{"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/collision-avoidance","display_name":"Collision avoidance","score":0.8074716329574585},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6834407448768616},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.5912870168685913},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5715288519859314},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4023175835609436},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2868560552597046},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1897139549255371}],"concepts":[{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.8074716329574585},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6834407448768616},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.5912870168685913},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5715288519859314},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4023175835609436},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2868560552597046},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1897139549255371}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651091","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":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W177987302","https://openalex.org/W1488757178","https://openalex.org/W1926863402","https://openalex.org/W1973396716","https://openalex.org/W1987935443","https://openalex.org/W1989407213","https://openalex.org/W2004815408","https://openalex.org/W2039107569","https://openalex.org/W2123030512","https://openalex.org/W2133067819","https://openalex.org/W2191404279","https://openalex.org/W2293119400","https://openalex.org/W2296073425","https://openalex.org/W2395575420","https://openalex.org/W2398043204","https://openalex.org/W2786928559","https://openalex.org/W2892258706","https://openalex.org/W2898567809","https://openalex.org/W2907234288","https://openalex.org/W2980480328","https://openalex.org/W2995937146","https://openalex.org/W2997307505","https://openalex.org/W3100930738","https://openalex.org/W3103635569","https://openalex.org/W3129616587","https://openalex.org/W3201099806","https://openalex.org/W3206082228","https://openalex.org/W4221155367","https://openalex.org/W4295402504","https://openalex.org/W4298857966","https://openalex.org/W4309679280","https://openalex.org/W4322759749","https://openalex.org/W4389689571","https://openalex.org/W6640227988","https://openalex.org/W6685444567","https://openalex.org/W6712181171","https://openalex.org/W6748554570","https://openalex.org/W6755542948","https://openalex.org/W6768539364","https://openalex.org/W6779753894","https://openalex.org/W6850691273","https://openalex.org/W6884305255"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2889566344","https://openalex.org/W4317634134","https://openalex.org/W2981729160","https://openalex.org/W4310743282","https://openalex.org/W2390279801","https://openalex.org/W1819938260","https://openalex.org/W2340892746","https://openalex.org/W3005999311"],"abstract_inverted_index":{"Multi-Agent":[0],"Path":[1],"Finding":[2],"(MAPF)":[3],"is":[4,207],"a":[5,9,93,140,146,215],"classic":[6],"problem":[7,64,82,199],"with":[8,16],"wide":[10],"range":[11],"of":[12,59,65,71,78,83,139,174,205],"applications.":[13],"To":[14,86],"cope":[15],"more":[17,66],"complex":[18],"situations":[19],"in":[20,105,214],"reality,":[21],"Dynamic":[22],"MAPF":[23],"(DMAPF)":[24],"has":[25],"received":[26],"much":[27],"attention.":[28],"The":[29,57,149,177],"existing":[30],"DMAPF":[31,46,198],"definition":[32],"lacks":[33],"completeness":[34],"or":[35],"considers":[36],"too":[37],"simple":[38],"situations.":[39],"In":[40],"this":[41,90],"paper,":[42],"we":[43],"comprehensively":[44],"model":[45],"based":[47],"on":[48],"realistic":[49],"scenarios.":[50],"Consequently,":[51],"dynamic":[52,216],"scenarios":[53],"bring":[54,62,80],"many":[55],"problems.":[56],"dynamics":[58,77],"agent":[60],"tasks":[61],"the":[63,72,76,81,133,155,162,170,197,203],"difficult":[67],"coordination":[68],"and":[69,75,108,127,145,161,188,202],"cooperation":[70,120],"multi-agent":[73,96],"system,":[74],"obstacles":[79],"increased":[84],"collisions.":[85],"address":[87],"these":[88],"problems,":[89],"paper":[91],"proposes":[92,109],"fully":[94],"decentralised":[95],"reinforcement":[97],"learning":[98],"method":[99],"CO3,":[100],"which":[101,123],"uses":[102],"COmmon":[103],"knowledge":[104,116],"selective":[106],"COmmunication":[107],"obstacle":[110,134,178],"COllision":[111],"avoidance":[112,136,142,151,180],"mechanism.":[113],"Firstly,":[114],"common":[115],"for":[117],"communication":[118],"improves":[119,124,154],"between":[121,130,186],"agents,":[122],"system":[125],"performance":[126],"reduces":[128],"collisions":[129,185,206],"agents.":[131],"Secondly,":[132],"collision":[135,141,150,179],"mechanism":[137,181],"consists":[138],"helper":[143,152],"module":[144,153],"critical":[147,163],"region.":[148],"agents\u2019":[156],"alertness":[157],"to":[158,169,172],"nearby":[159],"obstacles,":[160],"region":[164],"gives":[165],"an":[166],"early":[167],"warning":[168],"agents":[171,187],"beware":[173],"distant":[175],"obstacles.":[176,189],"can":[182,195],"effectively":[183],"reduce":[184],"Finally,":[190],"experiments":[191],"show":[192],"that":[193],"CO3":[194],"solve":[196],"quite":[200],"well,":[201],"number":[204],"significantly":[208],"lower":[209],"than":[210],"other":[211],"learning-based":[212],"methods":[213],"environment.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}