{"id":"W4389667406","doi":"10.1109/iros55552.2023.10342408","title":"Dynamic Decision Frequency with Continuous Options","year":2023,"lang":"en","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada); University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hyperparameter; Computer science; Reinforcement learning; Abstraction; Duration (music); Task (project management); Control (management); Action (physics); Variable (mathematics); Artificial intelligence; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001396239,0.0008031651,0.0007299443,0.0003691458,0.0003617624,0.0009720002,0.001387671,0.0009283862,0.002819871],"category_scores_gemma":[0.00555766,0.0003785657,0.0004274572,0.0003902285,0.001292523,0.001632187,0.001286141,0.001576851,0.0002847084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008298921,"about_ca_system_score_gemma":0.001018549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002635316,"about_ca_topic_score_gemma":0.002055381,"domain_scores_codex":[0.9992813,0.0002309921,0.00004288078,0.0001556159,0.0002051601,0.00008402554],"domain_scores_gemma":[0.9973499,0.001808559,0.0002414057,0.0002426213,0.0001775901,0.0001799345],"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":[0.0003370396,0.0001448926,0.001288655,0.0001052227,0.00003498458,0.0001153758,0.0001756982,0.8936866,0.002898077,0.0250378,0.0005714463,0.07560425],"study_design_scores_gemma":[0.00004404941,0.00006835297,0.000140959,0.00001025604,0.000007519597,0.00002560383,0.00001159222,0.9898858,0.0006796989,0.008507987,0.0006075463,0.00001061809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09374671,0.0004463676,0.8996291,0.0003425288,0.00009433139,0.000116071,0.00005418701,0.0006922166,0.004878494],"genre_scores_gemma":[0.9295291,0.0001024125,0.06861135,0.00008389782,0.00002188271,0.0001228097,0.00003665451,0.00003345777,0.001458491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002819871,"threshold_uncertainty_score":0.009433389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01068438737929049,"score_gpt":0.2540970301951204,"score_spread":0.2434126428158299,"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."}}