{"id":"https://openalex.org/W4391217630","doi":"https://doi.org/10.1007/s40747-023-01326-7","title":"Embedding multi-agent reinforcement learning into behavior trees with unexpected interruptions","display_name":"Embedding multi-agent reinforcement learning into behavior trees with unexpected interruptions","publication_year":2024,"publication_date":"2024-01-25","ids":{"openalex":"https://openalex.org/W4391217630","doi":"https://doi.org/10.1007/s40747-023-01326-7"},"language":"en","primary_location":{"id":"doi:10.1007/s40747-023-01326-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-023-01326-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-023-01326-7.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s40747-023-01326-7.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100660420","display_name":"Xianglong Li","orcid":"https://orcid.org/0009-0005-2805-8970"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xianglong Li","raw_affiliation_strings":["Academy of Military Sciences, Beijing, 100091, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, Beijing, 100091, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100716337","display_name":"Yuan Li","orcid":"https://orcid.org/0000-0002-6245-9437"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan Li","raw_affiliation_strings":["Academy of Military Sciences, Beijing, 100091, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, Beijing, 100091, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101741623","display_name":"Jieyuan Zhang","orcid":"https://orcid.org/0000-0003-2100-1312"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jieyuan Zhang","raw_affiliation_strings":["Academy of Military Sciences, Beijing, 100091, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, Beijing, 100091, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101775095","display_name":"Xinhai Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinhai Xu","raw_affiliation_strings":["Academy of Military Sciences, Beijing, 100091, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, Beijing, 100091, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102012605","display_name":"Donghong Liu","orcid":"https://orcid.org/0000-0001-7529-2253"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Donghong Liu","raw_affiliation_strings":["Academy of Military Sciences, Beijing, 100091, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences, Beijing, 100091, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100660420"],"corresponding_institution_ids":[],"apc_list":{"value":1320,"currency":"GBP","value_usd":1619},"apc_paid":{"value":1320,"currency":"GBP","value_usd":1619},"fwci":1.6724,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85236101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"10","issue":"3","first_page":"3273","last_page":"3282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9850000143051147,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9850000143051147,"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":0.9817000031471252,"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":0.9642000198364258,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7625183463096619},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6575064063072205},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.6424276232719421},{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.5599368214607239},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.520401120185852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.505387544631958},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3613009452819824},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.256328821182251},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.13400772213935852}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7625183463096619},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6575064063072205},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.6424276232719421},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.5599368214607239},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.520401120185852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.505387544631958},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3613009452819824},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.256328821182251},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.13400772213935852}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s40747-023-01326-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-023-01326-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-023-01326-7.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9b0cfb1787954f1287281e1a23a354d8","is_oa":true,"landing_page_url":"https://doaj.org/article/9b0cfb1787954f1287281e1a23a354d8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complex & Intelligent Systems, Vol 10, Iss 3, Pp 3273-3282 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s40747-023-01326-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-023-01326-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-023-01326-7.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3860502462","display_name":null,"funder_award_id":"62102444","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G610216879","display_name":null,"funder_award_id":"61902425","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391217630.pdf"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1642239575","https://openalex.org/W2007506196","https://openalex.org/W2521617762","https://openalex.org/W2770024602","https://openalex.org/W2784013554","https://openalex.org/W2894736632","https://openalex.org/W2898794805","https://openalex.org/W2948566565","https://openalex.org/W2963346735","https://openalex.org/W2997502221","https://openalex.org/W3007469703","https://openalex.org/W3008595109","https://openalex.org/W3024044737","https://openalex.org/W3133018151","https://openalex.org/W4210659600","https://openalex.org/W4287309212","https://openalex.org/W6600135713","https://openalex.org/W6636946117"],"related_works":["https://openalex.org/W2920061524","https://openalex.org/W4310083477","https://openalex.org/W1977959518","https://openalex.org/W2038908348","https://openalex.org/W2107890255","https://openalex.org/W2106552856","https://openalex.org/W2089013912","https://openalex.org/W2076061571","https://openalex.org/W1987513656","https://openalex.org/W2145821588"],"abstract_inverted_index":{"Abstract":[0],"Behavior":[1],"trees":[2,26],"have":[3],"attracted":[4],"great":[5],"interest":[6],"in":[7,98,130],"computer":[8],"games":[9],"and":[10,87,104],"robotic":[11],"applications.":[12],"However,":[13],"it":[14],"lacks":[15],"the":[16,39,43,74,82,88,101,124,157,160,164],"learning":[17,29,40,68,116,161],"ability":[18],"for":[19,50,147,172],"dynamic":[20],"environments.":[21],"Previous":[22],"works":[23],"combining":[24],"behavior":[25,71,78],"with":[27],"reinforcement":[28,67],"either":[30],"need":[31],"to":[32,110,144],"construct":[33],"an":[34,106,140],"independent":[35],"sub-scenario":[36],"or":[37],"train":[38],"method":[41],"over":[42],"whole":[44],"game,":[45],"which":[46],"is":[47,59,167],"not":[48],"suited":[49],"complex":[51],"multi-agent":[52,66],"games.":[53],"In":[54],"this":[55],"paper,":[56],"a":[57,95,173],"framework":[58,137],"proposed,":[60],"named":[61],"as":[62],"MARL-BT,":[63,99],"that":[64],"embeds":[65],"methods":[69],"into":[70],"trees.":[72],"Following":[73],"running":[75],"mechanism":[76],"of":[77,84,159],"trees,":[79],"we":[80,92,119],"design":[81],"way":[83],"collecting":[85],"samples":[86],"training":[89],"procedure.":[90],"Further,":[91],"point":[93],"out":[94],"special":[96],"phenomenon":[97],"i.e.,":[100,163],"unexpected":[102],"interruption,":[103],"present":[105],"action":[107,151],"masking":[108,152],"technique":[109,153],"remove":[111],"its":[112],"harmful":[113],"effect":[114],"on":[115,123],"performance.":[117],"Finally,":[118],"make":[120],"extensive":[121],"experiments":[122],"11":[125,127],"versus":[126],"full":[128],"game":[129],"Google":[131],"Research":[132],"Football.":[133],"The":[134,150],"introduced":[135],"MARL-BT":[136],"could":[138,154],"get":[139],"11.507%":[141],"improvement":[142],"compared":[143],"pure":[145],"BT":[146],"certain":[148],"scenarios.":[149],"greatly":[155],"improve":[156],"performance":[158],"method,":[162],"final":[165],"reward":[166],"improved":[168],"around":[169],"100%":[170],"times":[171],"sub-task.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}