{"id":"W4393404835","doi":"10.1109/tnet.2024.3383479","title":"Accurate Prediction of Network Distance via Federated Deep Reinforcement Learning","year":2024,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China; European Commission","keywords":"Reinforcement learning; Computer science; Artificial intelligence; Machine learning","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":[0.0009825025,0.001120887,0.001100347,0.0004215781,0.000361137,0.0008867646,0.00157884,0.0008281983,0.0008643109],"category_scores_gemma":[0.003593517,0.0004631867,0.0004589659,0.0003766219,0.0007280303,0.001216336,0.001381908,0.001651047,0.0002341883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001060759,"about_ca_system_score_gemma":0.001444147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01087699,"about_ca_topic_score_gemma":0.01146775,"domain_scores_codex":[0.9993882,0.0001063492,0.00003157811,0.0002031766,0.000159727,0.0001108758],"domain_scores_gemma":[0.9986162,0.0004936396,0.0002331351,0.000167298,0.000364343,0.000125315],"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":[0.00007383114,0.00006799179,0.00148471,0.00002619683,0.0000279952,0.00005633595,0.00003439143,0.9583427,0.001308224,0.001408522,0.0006938193,0.03647536],"study_design_scores_gemma":[0.000002969217,0.000009086661,0.00004982013,0.000001154694,0.000001717902,0.000003254041,0.000002082046,0.9991933,0.000168525,0.0005260923,0.00004063622,0.000001444655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07355661,0.0003453438,0.9223623,0.0002799385,0.00008475871,0.00004778539,0.00009121277,0.001343606,0.001888383],"genre_scores_gemma":[0.955639,0.00007805471,0.04280492,0.000109634,0.00001943886,0.00005952468,0.0001426548,0.00003880406,0.001107843],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01087699,"threshold_uncertainty_score":0.02162737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01716437586179162,"score_gpt":0.2490782694675083,"score_spread":0.2319138936057167,"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."}}