{"id":"W4320002923","doi":"10.1109/jiot.2023.3240173","title":"Cooperative UAV Resource Allocation and Task Offloading in Hierarchical Aerial Computing Systems: A MAPPO-Based Approach","year":2023,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Resource allocation; Resource management (computing); Task (project management); Distributed computing; Processor scheduling; Resource (disambiguation); Computer network; Real-time computing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005922384,0.0007689433,0.0008997155,0.00044022,0.0006662199,0.0009075134,0.001264012,0.0007615892,0.001532694],"category_scores_gemma":[0.001400612,0.0003936369,0.0004596655,0.000544122,0.0007803129,0.0009229906,0.001432657,0.0006830468,0.0001812034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007751416,"about_ca_system_score_gemma":0.001293999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006637522,"about_ca_topic_score_gemma":0.005737108,"domain_scores_codex":[0.9994468,0.0001246687,0.00002321824,0.0001457374,0.0001124967,0.0001470891],"domain_scores_gemma":[0.9994255,0.0002596959,0.0001006729,0.00006315426,0.0000729027,0.00007807978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007006256,0.00004938259,0.000786223,0.00007314718,0.00002536395,0.0001317485,0.0001028652,0.9669437,0.002728546,0.008829852,0.0005176261,0.01974137],"study_design_scores_gemma":[0.000004367025,0.00002039853,0.00009634588,0.000002857053,0.000005018962,0.000009767947,0.0000229916,0.9974573,0.0003018772,0.001823855,0.0002528437,0.000002327646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05322686,0.0004779424,0.9399805,0.0003559757,0.00006267928,0.0001091154,0.00006324743,0.0002325671,0.005491172],"genre_scores_gemma":[0.9459298,0.0001960473,0.05170235,0.00008370855,0.00004507992,0.0001094913,0.00004841215,0.00002994765,0.001855172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006637522,"threshold_uncertainty_score":0.01319778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01201198479428051,"score_gpt":0.2225579378625605,"score_spread":0.21054595306828,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}