{"id":"https://openalex.org/W7135020616","doi":"https://doi.org/10.48550/arxiv.2603.10436","title":"COHORT: Hybrid RL for Collaborative Large DNN Inference on Multi-Robot Systems Under Real-Time Constraints","display_name":"COHORT: Hybrid RL for Collaborative Large DNN Inference on Multi-Robot Systems Under Real-Time Constraints","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7135020616","doi":"https://doi.org/10.48550/arxiv.2603.10436"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10436","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10436","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.10436","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083697909","display_name":"Mohammad Saeid Anwar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anwar, Mohammad Saeid","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109114460","display_name":"Anuradha Ravi","orcid":"https://orcid.org/0000-0002-1678-1863"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ravi, Anuradha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026627445","display_name":"Indrajeet Ghosh","orcid":"https://orcid.org/0000-0003-2868-3766"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ghosh, Indrajeet","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078879236","display_name":"Gaurav Shinde","orcid":"https://orcid.org/0009-0004-5961-9526"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shinde, Gaurav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011446483","display_name":"Carl Busart","orcid":"https://orcid.org/0000-0002-1409-1068"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Busart, Carl","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5121814872","display_name":"Nirmalya Roy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roy, Nirmalya","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.2451000064611435,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.2451000064611435,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.20479999482631683,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.15449999272823334,"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/scalability","display_name":"Scalability","score":0.6171000003814697},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5692999958992004},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5655999779701233},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5429999828338623},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4521999955177307},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4212000072002411},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.40299999713897705},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.37779998779296875},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3725999891757965}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8119999766349792},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6171000003814697},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5692999958992004},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5655999779701233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5526000261306763},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5429999828338623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.517799973487854},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4521999955177307},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.37779998779296875},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3718000054359436},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.3716999888420105},{"id":"https://openalex.org/C2780102126","wikidata":"https://www.wikidata.org/wiki/Q10928179","display_name":"Online and offline","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C2780490138","wikidata":"https://www.wikidata.org/wiki/Q7079636","display_name":"Offline learning","level":3,"score":0.311599999666214},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C118070581","wikidata":"https://www.wikidata.org/wiki/Q2060528","display_name":"Neuroevolution","level":3,"score":0.2924000024795532},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2808000147342682},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.27219998836517334},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.2671000063419342},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.26570001244544983},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10436","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10436","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.10436","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10436","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4343235194683075,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"deep":[1],"neural":[2],"networks":[3],"(DNNs),":[4],"especially":[5],"transformer-based":[6],"and":[7,13,43,63,88,136,141,156,163,173,187,196],"multimodal":[8],"architectures,":[9],"are":[10,98],"computationally":[11],"demanding":[12],"challenging":[14],"to":[15,85],"deploy":[16],"on":[17,40,70,111,147],"resource-constrained":[18],"edge":[19],"platforms":[20],"like":[21],"field":[22],"robots.":[23,94],"These":[24],"challenges":[25],"intensify":[26],"in":[27,138],"mission-critical":[28],"scenarios":[29],"(e.g.,":[30],"disaster":[31],"response),":[32],"where":[33],"robots":[34],"must":[35],"collaborate":[36],"under":[37,165],"tight":[38],"constraints":[39,198],"bandwidth,":[41],"latency,":[42],"battery":[44,183],"life,":[45],"often":[46],"without":[47],"infrastructure":[48],"or":[49],"server":[50],"support.":[51],"To":[52],"address":[53],"these":[54],"limitations,":[55],"we":[56],"present":[57],"COHORT,":[58],"a":[59,78],"collaborative":[60],"DNN":[61,90,118],"inference":[62,151],"task-execution":[64],"framework":[65],"for":[66],"multi-robot":[67],"systems":[68],"built":[69],"the":[71,133,202],"Robotic":[72],"Operating":[73],"System":[74],"(ROS).":[75],"COHORT":[76,146,169,181],"employs":[77],"hybrid":[79],"offline-online":[80],"reinforcement":[81],"learning":[82,104],"(RL)":[83],"strategy":[84],"dynamically":[86],"schedule":[87],"distribute":[89],"module":[91],"execution":[92],"across":[93,120],"Our":[95],"key":[96],"contributions":[97],"threefold:":[99],"(a)":[100],"Offline":[101],"RL":[102,175],"policy":[103,125,135],"combined":[105],"with":[106,160],"Advantage-Weighted":[107],"Regression":[108],"(AWR),":[109],"trained":[110],"auction-based":[112],"task":[113],"allocation":[114],"data":[115],"from":[116,132],"heterogeneous":[117],"workloads":[119],"distributed":[121],"robots,":[122],"(b)":[123],"Online":[124],"adaptation":[126],"via":[127],"Multi-Agent":[128],"PPO":[129],"(MAPPO),":[130],"initialized":[131],"offline":[134],"fine-tuned":[137],"real":[139],"time,":[140],"(c)":[142],"comprehensive":[143],"evaluation":[144],"of":[145,201],"vision-language":[148],"model":[149],"(VLM)":[150],"tasks":[152],"such":[153],"as":[154],"CLIP":[155],"SAM,":[157],"analyzing":[158],"scalability":[159],"increasing":[161],"robot/workload":[162],"robustness":[164],".":[166],"We":[167],"benchmark":[168],"against":[170],"genetic":[171],"algorithms":[172],"multiple":[174],"baselines.":[176],"Experimental":[177],"results":[178],"demonstrate":[179],"that":[180],"reduces":[182],"consumption":[184],"by":[185,191],"15.4%":[186],"increases":[188],"GPU":[189],"utilization":[190],"51.67%,":[192],"while":[193],"satisfying":[194],"frame-rate":[195],"deadline":[197],"2.55":[199],"times":[200],"time.":[203]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-13T00:00:00"}