{"id":"W2967515641","doi":"10.1109/rose.2019.8790424","title":"Neurofuzzy Reinforcement Learning Control Schemes for Optimized Dynamical Performance","year":2019,"lang":"en","type":"article","venue":"","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Reinforcement learning; Computer science; Control (management); 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":[0.0008110034,0.0005766419,0.0004118856,0.0002248353,0.0002225992,0.0004776198,0.0007579207,0.00049519,0.001608061],"category_scores_gemma":[0.001234563,0.0001494813,0.0002285516,0.0002814785,0.0004784323,0.0004590142,0.000458543,0.0007146918,0.0002914373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005764436,"about_ca_system_score_gemma":0.0004933588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001692113,"about_ca_topic_score_gemma":0.001925381,"domain_scores_codex":[0.9998009,0.00004767774,0.00001299516,0.00003630291,0.00008158447,0.00002049829],"domain_scores_gemma":[0.999552,0.0001879207,0.00008799906,0.00004604741,0.0001113412,0.00001474575],"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":[0.00008738597,0.0001187649,0.0002871472,0.0001390107,0.00003245419,0.00007431587,0.0001083561,0.8316129,0.02119149,0.0230409,0.001138983,0.1221682],"study_design_scores_gemma":[0.00001193738,0.00004203141,0.00007448601,0.000005723087,0.000003863618,0.00001255284,0.000002791264,0.995333,0.0021456,0.001563967,0.0007985899,0.000005421472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01857833,0.0002848688,0.9770793,0.00009454925,0.00004981607,0.00005701415,0.00001092461,0.0002658496,0.003579357],"genre_scores_gemma":[0.8913739,0.0001687071,0.10474,0.0000540595,0.00002743375,0.0001224241,0.00001744279,0.00002800646,0.003468033],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001692113,"threshold_uncertainty_score":0.005379558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006745649804198587,"score_gpt":0.2209946881010428,"score_spread":0.2142490382968442,"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."}}