{"id":"W2017555899","doi":"10.1109/med.2012.6265646","title":"Q(&amp;#x03BB;)-learning fuzzy controller for the homicidal chauffeur differential game","year":2012,"lang":"en","type":"article","venue":"","topic":"Guidance and Control Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Pursuer; Differential game; Fuzzy logic; Computer science; Controller (irrigation); Differential (mechanical device); Artificial intelligence; Fuzzy control system; Control theory (sociology); Mathematical optimization; Mathematics; Engineering; Control (management)","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":[0.0007994773,0.0003747186,0.000401589,0.0002275943,0.0005351665,0.0005948322,0.0008200243,0.0007051061,0.001805954],"category_scores_gemma":[0.001606398,0.0001243608,0.0002427544,0.0001721367,0.0006610917,0.0003586444,0.0004763109,0.0007704969,0.0002539328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007705854,"about_ca_system_score_gemma":0.0007655293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01067197,"about_ca_topic_score_gemma":0.006884357,"domain_scores_codex":[0.9997829,0.00005011694,0.00001283579,0.00004659719,0.00007598,0.00003149702],"domain_scores_gemma":[0.9996411,0.0001572527,0.00004178839,0.00001803942,0.0001182942,0.00002345574],"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":[0.0001843959,0.0001671538,0.001404544,0.0001673397,0.00006214491,0.0003345512,0.0003513444,0.7947093,0.01587904,0.03559541,0.001540657,0.1496042],"study_design_scores_gemma":[0.0000263653,0.00008184771,0.0001874058,0.0000076303,0.00000926628,0.00003470859,0.000009674688,0.994484,0.001301294,0.003115234,0.0007321991,0.00001027072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0358176,0.0001469274,0.9570996,0.0001770845,0.00005959622,0.00007733491,0.00001772703,0.0003369072,0.006267184],"genre_scores_gemma":[0.9485213,0.0001005245,0.04823654,0.0001247647,0.00001682242,0.0001088334,0.0000165185,0.00000949374,0.002865172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01067197,"threshold_uncertainty_score":0.02121973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01423167963072518,"score_gpt":0.2155381560580866,"score_spread":0.2013064764273614,"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."}}