{"id":"W2096827855","doi":"10.1016/j.automatica.2009.03.013","title":"Robust guaranteed cost control for uncertain stochastic systems with multiple decision makers","year":2009,"lang":"en","type":"article","venue":"Automatica","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Karush–Kuhn–Tucker conditions; Mathematical optimization; Mathematics; Linear matrix inequality; Control theory (sociology); Controller (irrigation); Riccati equation; Upper and lower bounds; Stochastic control; Cost control; Optimal control; Computation; Control (management); Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003581404,0.0002744512,0.0005297495,0.00009023742,0.0001142292,0.0001118688,0.0002176902,0.0001188489,0.00001017534],"category_scores_gemma":[0.0002486116,0.0002175554,0.0001030736,0.000171515,0.00004202014,0.0001130272,0.000004477874,0.0001096536,0.00003207287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001547981,"about_ca_system_score_gemma":0.0000370375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003178477,"about_ca_topic_score_gemma":0.00003695066,"domain_scores_codex":[0.9984331,0.00004018837,0.0004944857,0.0002612447,0.0003044686,0.0004665139],"domain_scores_gemma":[0.9979771,0.001308005,0.00007346197,0.0004134029,0.0001039649,0.0001240623],"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":[0.0003248874,0.00004374995,0.0001120415,0.0001418755,0.0001052738,0.000006298629,0.0002389745,0.9901012,0.0003539125,0.0007655738,0.0009096071,0.006896632],"study_design_scores_gemma":[0.004971733,0.0002825808,0.001059347,0.0003302595,0.00007446728,0.00002543479,0.000380753,0.9915411,0.00001108514,0.0002223596,0.0008101073,0.0002907706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03158563,0.0004549835,0.9632972,0.0001556564,0.0004097745,0.002787541,0.00006977079,0.0007810498,0.0004583547],"genre_scores_gemma":[0.9961945,0.000001100997,0.003087195,0.0001133919,0.0001125292,0.0004098419,0.00001035306,0.00003816812,0.00003292379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9646088,"threshold_uncertainty_score":0.887165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650515444694709,"score_gpt":0.2201561177301996,"score_spread":0.2036509632832525,"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."}}