{"id":"W4390422128","doi":"10.1109/jiot.2023.3348590","title":"Multitimescale Control and Communications With Deep Reinforcement Learning—Part I: Communication-Aware Vehicle Control","year":2023,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Guelph","funders":"","keywords":"Computer science; Reinforcement learning; Control (management); Computer network; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008216058,0.0009619389,0.001004018,0.0002345078,0.0003378717,0.0009147453,0.001025292,0.001318495,0.001610644],"category_scores_gemma":[0.002016086,0.0005084816,0.0004741247,0.0003630129,0.001201911,0.001116329,0.001418584,0.002088507,0.0001872069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187812,"about_ca_system_score_gemma":0.001957569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009619836,"about_ca_topic_score_gemma":0.005182665,"domain_scores_codex":[0.9994751,0.0001048962,0.00002529173,0.0001674064,0.0001198833,0.0001075227],"domain_scores_gemma":[0.9992719,0.0003899531,0.0001117562,0.00006571539,0.0001048268,0.0000557864],"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":[0.00004338013,0.00004395407,0.0004893042,0.00006952981,0.00002600683,0.00004770195,0.00003749672,0.9568735,0.001416647,0.006504694,0.0008054674,0.03364234],"study_design_scores_gemma":[0.000003553699,0.000012381,0.00004449576,0.000002925965,0.000002380291,0.000003894575,0.000002343766,0.9984774,0.0002169747,0.001071016,0.0001606894,0.000001902811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02539254,0.0006611704,0.9695346,0.0006418145,0.00007477419,0.00005306382,0.00004085091,0.0004009035,0.003200331],"genre_scores_gemma":[0.9431693,0.0004166175,0.0530678,0.0002899519,0.00009382948,0.0001412905,0.00009588445,0.00004880728,0.002676482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009619836,"threshold_uncertainty_score":0.01912767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008489308438021075,"score_gpt":0.2202001670619521,"score_spread":0.211710858623931,"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."}}