{"id":"W3112168663","doi":"10.1109/smc42975.2020.9283399","title":"Trajectory Tracking of Underactuated Sea Vessels With Uncertain Dynamics: An Integral Reinforcement Learning Approach","year":2020,"lang":"en","type":"article","venue":"","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Rudder; Trajectory; Underactuation; Reinforcement learning; Control theory (sociology); Computer science; Tracking error; Tracking (education); Gradient descent; Process (computing); Thrust; Artificial intelligence; Robot; Control (management); Engineering; Artificial neural network; Physics","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":[0.0007659241,0.0004415112,0.0005597168,0.0002125754,0.0002460951,0.0004761742,0.0006848348,0.0005474449,0.0007521226],"category_scores_gemma":[0.001582566,0.0002383869,0.0002418069,0.0001604788,0.0008203459,0.0004304502,0.0006240877,0.0007768243,0.00008833281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004996896,"about_ca_system_score_gemma":0.0006653779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005391871,"about_ca_topic_score_gemma":0.002496798,"domain_scores_codex":[0.9998338,0.00005381803,0.000007299952,0.0000324547,0.00004296107,0.00002963987],"domain_scores_gemma":[0.9993895,0.0003291297,0.00009840378,0.00003558661,0.0001091922,0.00003813719],"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":[0.0000296676,0.00001873992,0.0002768603,0.00001956758,0.00001345179,0.00004002535,0.00004074104,0.9826655,0.00144849,0.004962632,0.000106281,0.01037791],"study_design_scores_gemma":[0.000001951697,0.000009335226,0.00002233332,7.584684e-7,0.000001223599,0.000001883829,0.000001150187,0.9993051,0.0001019151,0.0005142848,0.00003919179,9.494518e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08472581,0.0001675858,0.9120876,0.0001653563,0.00002700752,0.00002409289,0.00001146989,0.0001630335,0.002628116],"genre_scores_gemma":[0.9763178,0.00007088407,0.02241887,0.00002201655,0.0000142566,0.00003314311,0.00001022236,0.00001080133,0.00110201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005391871,"threshold_uncertainty_score":0.01072097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02888362439632784,"score_gpt":0.2476196000962814,"score_spread":0.2187359756999536,"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."}}