{"id":"https://openalex.org/W7162083550","doi":"https://doi.org/10.48550/arxiv.2605.22306","title":"ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps","display_name":"ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps","publication_year":2026,"publication_date":"2026-05-21","ids":{"openalex":"https://openalex.org/W7162083550","doi":"https://doi.org/10.48550/arxiv.2605.22306"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.22306","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22306","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.22306","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046815415","display_name":"Cezary Adamczyk","orcid":"https://orcid.org/0000-0002-0634-8935"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adamczyk, Cezary","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5011947791","display_name":"Adrian Kliks","orcid":"https://orcid.org/0000-0001-6766-7836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kliks, Adrian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.6980000138282776,"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"}},"topics":[{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.6980000138282776,"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"}},{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.08730000257492065,"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"}},{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.048900000751018524,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7634999752044678},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5898000001907349},{"id":"https://openalex.org/keywords/conflict-resolution","display_name":"Conflict resolution","score":0.5564000010490417},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.5361999869346619},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.5042999982833862},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4171000123023987}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7634999752044678},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6347000002861023},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5990999937057495},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5898000001907349},{"id":"https://openalex.org/C21711469","wikidata":"https://www.wikidata.org/wiki/Q1194317","display_name":"Conflict resolution","level":2,"score":0.5564000010490417},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.5361999869346619},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.5042999982833862},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.424699991941452},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4171000123023987},{"id":"https://openalex.org/C82327864","wikidata":"https://www.wikidata.org/wiki/Q835100","display_name":"Intelligent control","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35679998993873596},{"id":"https://openalex.org/C74925373","wikidata":"https://www.wikidata.org/wiki/Q4175911","display_name":"Control network","level":3,"score":0.3427000045776367},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28209999203681946},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.22306","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22306","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.22306","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22306","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5170072317123413}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Conflict":[0,39],"Mitigation":[1],"(ConMit)":[2],"is":[3,103,115],"a":[4,22,38,51],"crucial":[5],"part":[6],"of":[7,99,128],"intelligent":[8],"network":[9,63,80,135],"control":[10,29,66,140],"in":[11,31,142],"Open":[12],"Radio":[13],"Access":[14],"Networks":[15],"(O-RAN).":[16],"In":[17],"this":[18],"paper,":[19],"we":[20],"propose":[21],"method":[23,123],"named":[24],"ACCoRD":[25],"to":[26,68,85],"resolve":[27],"detected":[28],"conflicts":[30],"Near-Real":[32],"Time":[33],"RAN":[34],"Intelligent":[35],"Controller":[36],"using":[37],"Resolution":[40],"(CR)":[41],"Agent":[42,75],"with":[43,50],"an":[44],"Artificial":[45],"Neural":[46],"Network":[47],"(ANN)":[48],"trained":[49],"reinforcement":[52],"learning":[53],"algorithm":[54],"PPO-Clip.":[55],"The":[56,73,97],"implemented":[57],"ANN":[58],"analyzes":[59],"data":[60],"about":[61],"the":[62,79,91,100,120,126],"and":[64,89,144],"conflicting":[65,139],"decisions":[67,141],"infer":[69],"optimal":[70],"CR":[71,74,113],"actions.":[72],"gathers":[76],"feedback":[77],"from":[78],"after":[81],"each":[82],"resolved":[83],"conflict":[84],"assess":[86],"its":[87],"efficiency":[88,127],"adjust":[90],"ANN's":[92],"weights":[93],"during":[94],"batch":[95],"training.":[96],"evaluation":[98],"proposed":[101,121],"approach":[102],"based":[104],"on":[105,125],"simulation":[106],"data.":[107],"A":[108],"new":[109],"methodology":[110],"for":[111],"evaluating":[112],"solutions":[114],"proposed.":[116],"Results":[117],"show":[118],"that":[119],"ANN-based":[122],"improves":[124],"rule-based":[129],"approaches":[130],"by":[131,138],"significantly":[132],"reducing":[133],"negative":[134],"events":[136],"caused":[137],"medium":[143],"high":[145],"traffic":[146],"scenarios.":[147]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-23T00:00:00"}
