{"id":"W1910412336","doi":"10.1002/oca.2190","title":"Symmetries and analytical solutions of the Hamilton–Jacobi–Bellman equation for a class of optimal control problems","year":2015,"lang":"en","type":"article","venue":"Optimal Control Applications and Methods","topic":"Sphingolipid Metabolism and Signaling","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hamilton–Jacobi–Bellman equation; Mathematics; Optimal control; Riccati equation; Bellman equation; Differentiable function; Homogeneous space; Applied mathematics; Affine transformation; Ordinary differential equation; Differential equation; Adjoint equation; Partial differential equation; Mathematical analysis; Mathematical optimization; Pure mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001394942,0.0005611952,0.0007159683,0.0005212166,0.0004807379,0.001173867,0.0005887633,0.001026032,0.003073204],"category_scores_gemma":[0.002194908,0.0003486052,0.001126014,0.0003194624,0.00163223,0.001123538,0.0009785962,0.001702445,0.0003498296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001213428,"about_ca_system_score_gemma":0.001279499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002236234,"about_ca_topic_score_gemma":0.001035753,"domain_scores_codex":[0.999536,0.0001584222,0.00002309839,0.0000709019,0.0001566692,0.00005481206],"domain_scores_gemma":[0.9993631,0.0003163276,0.0001364566,0.00006067747,0.00008860192,0.00003488956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009117932,0.00002111552,0.0002294637,0.00004972317,0.00001844648,0.00007397865,0.0001167011,0.07297561,0.002552625,0.916881,0.0007417331,0.006330519],"study_design_scores_gemma":[0.00001395153,0.00002995941,0.0002628914,0.00001608676,0.000006798413,0.00005512781,0.00005884274,0.6432256,0.0005724276,0.353794,0.001950053,0.0000142569],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05544949,0.0007792104,0.9099548,0.001219403,0.00009621693,0.00008054719,0.00007437423,0.00007557629,0.0322703],"genre_scores_gemma":[0.874454,0.001042768,0.1093903,0.0002451353,0.0001584365,0.0002813996,0.0001527676,0.0000721043,0.01420307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003073204,"threshold_uncertainty_score":0.01028091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03747302974969471,"score_gpt":0.3285363041298008,"score_spread":0.291063274380106,"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."}}