{"id":"W2897394476","doi":"10.1016/j.neunet.2018.10.007","title":"Implicit incremental natural actor critic algorithm","year":2018,"lang":"en","type":"article","venue":"Neural Networks","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Core Research for Evolutional Science and Technology; Indigenous and Northern Affairs Canada","keywords":"Convergence (economics); Computer science; Stability (learning theory); Algorithm; Sensitivity (control systems); Natural (archaeology); Mathematical optimization; Mathematics; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009881256,0.0008406506,0.001185205,0.0005050186,0.0004139756,0.0009098137,0.001969224,0.001097486,0.00381248],"category_scores_gemma":[0.003539223,0.0004311475,0.0004555521,0.0004118357,0.0006528595,0.0008772163,0.00120484,0.001247922,0.0008346658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000636059,"about_ca_system_score_gemma":0.001740169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004734048,"about_ca_topic_score_gemma":0.005679788,"domain_scores_codex":[0.9994392,0.0001588277,0.00002837805,0.0001139468,0.0001826918,0.00007696853],"domain_scores_gemma":[0.9989049,0.0004773329,0.00009326662,0.0001112388,0.0003551124,0.00005811798],"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":[0.0001996334,0.00007234912,0.001124115,0.0002038624,0.00006891668,0.0001899953,0.000140347,0.7964768,0.002248776,0.02759874,0.005079709,0.1665968],"study_design_scores_gemma":[0.00001420009,0.00001694791,0.0000588783,0.000005030485,0.000007039861,0.00002009421,0.000003491444,0.9963237,0.0002587135,0.002392477,0.0008948438,0.000004733385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01051657,0.000347355,0.9805555,0.0001938467,0.0001045906,0.00009061591,0.00006078961,0.000735007,0.007395806],"genre_scores_gemma":[0.7095523,0.0003838077,0.2757266,0.0003547402,0.0001226558,0.0004238065,0.0003144857,0.0001817297,0.01293992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004734048,"threshold_uncertainty_score":0.01275408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007517203886446978,"score_gpt":0.2562019818367436,"score_spread":0.2486847779502966,"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."}}