{"id":"W4312294756","doi":"10.1016/j.procs.2022.10.107","title":"A TD-Learning Based Bionic Cerebellar Model Controller For Humanoid Robots","year":2022,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"National University's Basic Research Foundation of China; Department of Education of Liaoning Province; Natural Science Foundation of Liaoning Province; Science and Technology Commission of Shanghai Municipality; China Postdoctoral Science Foundation","keywords":"Computer science; Humanoid robot; Robot; Process (computing); Artificial intelligence; Cerebellum; Reinforcement learning; Simulation; Neuroscience","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":[0.0002005327,0.0004249205,0.0003817864,0.000209373,0.0004095647,0.0004354734,0.0007249508,0.0004481492,0.002297982],"category_scores_gemma":[0.0004315128,0.0001422393,0.0002684734,0.0001648877,0.0003313513,0.0003268895,0.0003825476,0.0003524971,0.0003302276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004075216,"about_ca_system_score_gemma":0.0006339563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007744338,"about_ca_topic_score_gemma":0.005865294,"domain_scores_codex":[0.9998974,0.00001345521,0.000008363314,0.00003341582,0.0000342553,0.00001316252],"domain_scores_gemma":[0.9998686,0.00002438101,0.00002392048,0.00001272124,0.00005862556,0.00001159803],"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":[0.000379714,0.0001734951,0.00112758,0.0005103771,0.0001136693,0.0004983695,0.0002681853,0.6124622,0.0603742,0.01274401,0.00473472,0.3066135],"study_design_scores_gemma":[0.00005349025,0.0002351868,0.0003509012,0.00001855322,0.00002514913,0.0001009133,0.00001492346,0.9913703,0.003590274,0.0009925844,0.003234201,0.00001351413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04404896,0.0007063869,0.939985,0.0002171217,0.000251106,0.0001051222,0.00005450518,0.001558296,0.01307356],"genre_scores_gemma":[0.9504053,0.0002412669,0.0444686,0.00008471026,0.00002945757,0.0001365483,0.00005611771,0.00003193968,0.004546047],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007744338,"threshold_uncertainty_score":0.0153985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008869988027543456,"score_gpt":0.1988751749000063,"score_spread":0.1900051868724628,"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."}}