{"id":"W4400771720","doi":"10.1109/tvt.2024.3429507","title":"Joint Data Caching and Computation Offloading in UAV-Assisted Internet of Vehicles via Federated Deep Reinforcement Learning","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Science Foundation of Beijing Municipality","keywords":"Reinforcement learning; Computer science; Computation offloading; Joint (building); The Internet; Computation; Computer network; Artificial intelligence; Internet of Things; Embedded system; Engineering; World Wide Web; Edge computing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004087306,0.0001672856,0.0002439578,0.0009122892,0.0001548617,0.0001306256,0.0004025218,0.0001779479,0.000001506028],"category_scores_gemma":[0.00001353095,0.0001711382,0.00004108975,0.0009235342,0.00007532662,0.0003511826,0.00004335816,0.0006530582,0.00000914811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009742736,"about_ca_system_score_gemma":0.00004077817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001450007,"about_ca_topic_score_gemma":0.000030041,"domain_scores_codex":[0.998534,0.00008150953,0.0004335758,0.0005214818,0.000166987,0.0002624097],"domain_scores_gemma":[0.9994227,0.00009173161,0.00008413535,0.0003170928,0.00004909136,0.00003521295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001229255,0.00008367371,0.00009004486,0.0001512252,0.0001172149,0.0001168323,0.001093273,0.2412106,0.04154022,0.0003253286,0.00004128378,0.7152179],"study_design_scores_gemma":[0.0002524611,0.0001344355,0.0001211109,0.0002910178,0.00001677154,0.0001068457,0.00005616384,0.9663445,0.0320824,0.0002613907,0.0001788198,0.0001540604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.212709,0.0002422527,0.7851059,0.0004376748,0.000953329,0.0001263875,1.5632e-7,0.0003915057,0.00003378083],"genre_scores_gemma":[0.9924591,0.00002204998,0.007408182,0.00002646475,0.00002988679,0.000008461891,0.000007409845,0.00001517489,0.0000232964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7797501,"threshold_uncertainty_score":0.6978813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02812423264757062,"score_gpt":0.2657956614659048,"score_spread":0.2376714288183342,"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."}}