{"id":"W2159683855","doi":"10.1109/robot.2005.1570827","title":"Learning to Steer on Winding Tracks Using Semi-Parametric Control Policies","year":2006,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Voronoi diagram; Parametric statistics; Nonholonomic system; Representation (politics); Computer science; Control (management); Set (abstract data type); Truck; Node (physics); Reinforcement learning; State space; Vehicle dynamics; Control theory (sociology); State (computer science); Space (punctuation); Artificial intelligence; Mobile robot; Engineering; Robot; Mathematics; Algorithm","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":[0.0004001486,0.0001850004,0.0002329423,0.0005694189,0.0002323177,0.0003048627,0.0005411783,0.00007382657,0.00000833709],"category_scores_gemma":[0.0001555757,0.0001671323,0.00006200201,0.001268947,0.00001961008,0.0002645206,0.00009008121,0.0002425629,0.0001526961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001300798,"about_ca_system_score_gemma":0.00004097799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004807785,"about_ca_topic_score_gemma":0.000001568715,"domain_scores_codex":[0.9982704,0.00009312157,0.0002636954,0.0004117039,0.0004306068,0.00053047],"domain_scores_gemma":[0.9990348,0.0003599534,0.000088193,0.0003393241,0.00005926163,0.0001184228],"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":[0.000003260729,0.00003704434,0.007385649,0.000003053542,0.000009553992,0.00002696612,0.0004010044,0.9832839,0.001596179,0.002971567,0.0004944992,0.003787326],"study_design_scores_gemma":[0.0004443619,0.0001984025,0.01772836,0.00004419257,0.000008120849,0.00003787419,0.00008660287,0.9788367,0.001545699,0.0001647846,0.0006008875,0.0003040011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2144346,0.00001941271,0.7770922,0.0003877063,0.0002711284,0.0001518761,7.662695e-7,0.0003279726,0.007314338],"genre_scores_gemma":[0.8361421,2.009295e-7,0.1613621,0.0005597185,0.0001610183,0.000003755651,6.952173e-7,0.00001354921,0.001756855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6217075,"threshold_uncertainty_score":0.6815455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02052727492655067,"score_gpt":0.2697594599214931,"score_spread":0.2492321849949424,"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."}}