{"id":"W1982679994","doi":"10.1142/s0129183102003450","title":"FUZZY REINFORCEMENT LEARNING","year":2002,"lang":"en","type":"article","venue":"International Journal of Modern Physics C","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Fuzzy logic; Artificial intelligence; Computer science; Reinforcement learning; Extension (predicate logic); Adaptive neuro fuzzy inference system; Neuro-fuzzy; Inference; Fuzzy inference; Knowledge base; Fuzzy set operations; Fuzzy control system; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009995556,0.00006372116,0.00007645132,0.00005439408,0.00006155741,0.00008199609,0.0008137266,0.00001751995,0.0000220289],"category_scores_gemma":[0.0000142453,0.00005901304,0.00009118758,0.00008551176,0.00001738235,0.0005919579,0.0001123458,0.0001727356,0.00005218647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006063913,"about_ca_system_score_gemma":0.00001998434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001620156,"about_ca_topic_score_gemma":8.324538e-8,"domain_scores_codex":[0.9990473,0.00001592175,0.0002517001,0.00009042479,0.0005022257,0.00009241728],"domain_scores_gemma":[0.9991443,0.00003730339,0.0002583516,0.0001140332,0.0003942593,0.00005174684],"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":[0.000004885844,0.0002528402,0.0002900155,0.000001963594,0.0001397184,0.0000313595,0.001070704,0.2542495,0.001910039,0.3298719,0.003389264,0.4087878],"study_design_scores_gemma":[0.0003734725,0.00006156968,0.0002544587,0.0000203017,0.000004622742,0.00009676381,0.000009107037,0.8320364,0.0005174737,0.1571911,0.009341686,0.00009304882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002419752,0.000156653,0.9857961,0.002317981,0.0003565736,0.00002489918,4.8564e-7,0.00002033856,0.008907249],"genre_scores_gemma":[0.9788605,0.00009316661,0.01956165,0.0001810704,0.0005590658,0.000002040057,0.000001254442,0.00000453519,0.0007367296],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9764407,"threshold_uncertainty_score":0.2406482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02363624726713457,"score_gpt":0.2581544148872441,"score_spread":0.2345181676201095,"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."}}