{"id":"W4404954737","doi":"10.1109/ssrr62954.2024.10770028","title":"Monte Carlo Tree Search for Behavior Planning in Autonomous Driving","year":2024,"lang":"en","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Monte Carlo tree search; Monte Carlo method; Computer science; Tree (set theory); Artificial intelligence; Mathematics; Statistics","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":[0.001049396,0.0004840165,0.0006510089,0.000697011,0.0004614459,0.0006170898,0.0008062446,0.0008259593,0.001469023],"category_scores_gemma":[0.004798194,0.0004041517,0.0004489237,0.0006342065,0.0009159859,0.000718612,0.0006853921,0.0008236074,0.0002592546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001142648,"about_ca_system_score_gemma":0.001728944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009830876,"about_ca_topic_score_gemma":0.009417708,"domain_scores_codex":[0.9996219,0.0001659837,0.00001748177,0.00005378579,0.00009841662,0.00004234752],"domain_scores_gemma":[0.9982935,0.001311042,0.00009725988,0.00005322311,0.0001757664,0.00006931534],"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":[0.00002524195,0.00001259155,0.0004500762,0.00001878436,0.00001103236,0.00001481926,0.00002470454,0.9790162,0.000314344,0.007852055,0.0002545511,0.01200576],"study_design_scores_gemma":[0.000002625604,0.000005169068,0.00002636017,0.000001923484,0.000001066228,0.000002496991,0.000001854591,0.9978728,0.00005929467,0.001914719,0.0001104586,0.000001147138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03015642,0.0003424289,0.9658903,0.0002237898,0.00003161493,0.00005054089,0.00004162157,0.0003465768,0.002916766],"genre_scores_gemma":[0.7310504,0.0002354107,0.2663734,0.0001358726,0.00003318334,0.0002080512,0.0001480635,0.00009126562,0.001724347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009830876,"threshold_uncertainty_score":0.01954728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0393457966540007,"score_gpt":0.3198587520506013,"score_spread":0.2805129553966006,"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."}}