{"id":"W2954371384","doi":"10.1155/2019/1019078","title":"Hierarchical Sarsa Learning Based Route Guidance Algorithm","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Reinforcement learning; Cluster analysis; State space; Scale (ratio); Task (project management); State (computer science); Artificial intelligence; Differential (mechanical device); Algorithm; Engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004505094,0.0006615694,0.0008402983,0.0006084194,0.000528188,0.0007189298,0.001403013,0.001088507,0.004186963],"category_scores_gemma":[0.001173666,0.0003478696,0.0006158451,0.0004724559,0.0005701481,0.0008058175,0.000939588,0.0008917582,0.0007899879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007132565,"about_ca_system_score_gemma":0.001542031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01273051,"about_ca_topic_score_gemma":0.009177372,"domain_scores_codex":[0.9996369,0.00006156727,0.00002170795,0.000109726,0.00009866629,0.00007140846],"domain_scores_gemma":[0.9995633,0.0001269929,0.00006060414,0.00003771367,0.0001767499,0.00003466341],"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":[0.00006032872,0.00004463102,0.0008109428,0.00004721295,0.00003121329,0.00004842439,0.00007111674,0.9145169,0.001943885,0.005599696,0.001329108,0.07549658],"study_design_scores_gemma":[0.000009603595,0.00002021641,0.00005995559,0.000002635798,0.000003456098,0.00001008129,0.000006983346,0.9984052,0.0002476202,0.0008386412,0.0003927783,0.000002827157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03085073,0.00031724,0.9601264,0.0002004215,0.00006820343,0.00008111657,0.00007839595,0.000989854,0.007287654],"genre_scores_gemma":[0.823813,0.0001978029,0.1683122,0.0002015471,0.00003971832,0.0002123162,0.0003095382,0.00007597444,0.006838003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01273051,"threshold_uncertainty_score":0.02531284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003394400610267142,"score_gpt":0.2048275990718651,"score_spread":0.201433198461598,"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."}}