{"id":"W2377441786","doi":"","title":"Reinforcement learning algorithm based on general fuzzifiedcerebellar model articulation controller","year":2004,"lang":"en","type":"article","venue":"Systems engineering and electronics","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Cerebellar model articulation controller; Reinforcement learning; Computer science; Field (mathematics); Controller (irrigation); Articulation (sociology); Reinforcement; Control theory (sociology); Artificial intelligence; Algorithm; Control (management); Engineering; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000144894,0.0002496064,0.000285852,0.0000860298,0.00008608602,0.00005837056,0.00005379293,0.0001113759,8.270641e-7],"category_scores_gemma":[0.00001197575,0.0002469575,0.00005878734,0.0001047852,0.000006704116,0.00007689146,0.000005523807,0.000283487,0.000007515417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002862685,"about_ca_system_score_gemma":0.00002181228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001443033,"about_ca_topic_score_gemma":9.591895e-7,"domain_scores_codex":[0.998804,0.00001259677,0.0002965499,0.0001975277,0.0002170139,0.0004722788],"domain_scores_gemma":[0.9996537,0.00002450975,0.00003538021,0.0001475884,0.0000338041,0.0001050352],"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":[0.000008177782,0.000005092375,0.000003357148,0.00006266822,0.00003747495,0.000002057041,0.000046569,0.9875062,0.00823757,0.003329862,0.00001533545,0.0007456888],"study_design_scores_gemma":[0.001335285,0.0001072194,0.000006531362,0.00006869242,0.00001831797,0.000009412765,0.00001616479,0.9955059,0.0006548895,0.00004707708,0.001957284,0.0002732044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02509418,0.002960345,0.9703208,0.00001410878,0.0002554087,0.0003207198,0.000002303306,0.0005588468,0.0004733361],"genre_scores_gemma":[0.9982802,0.0001258536,0.001130952,0.00001618856,0.000176707,0.00005284878,0.00001565524,0.00006102538,0.0001405607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.973186,"threshold_uncertainty_score":0.9999983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003740636381374708,"score_gpt":0.1735484543960202,"score_spread":0.1698078180146455,"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."}}