{"id":"W1861432007","doi":"10.23919/ecc.2013.6669512","title":"Distributed estimation and control for large population stochastic multi-agent systems with coupling in the measurements","year":2013,"lang":"en","type":"article","venue":"","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Linear-quadratic-Gaussian control; Control theory (sociology); Kalman filter; Computer science; Population; State (computer science); Gaussian; Exponential stability; Stability (learning theory); Controller (irrigation); Linear system; Quadratic equation; Exponential function; Coupling (piping); Mathematical optimization; Mathematics; Nonlinear system; Optimal control; Control (management); Algorithm; Engineering; Artificial intelligence; Machine learning","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":[0.001884876,0.0007455905,0.001083305,0.0003796279,0.0005405729,0.001128108,0.001121883,0.001091084,0.0006182878],"category_scores_gemma":[0.005714484,0.0004787577,0.0007089826,0.0005361236,0.001282877,0.001308199,0.001496656,0.001313255,0.0001058797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00101114,"about_ca_system_score_gemma":0.000989165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005768456,"about_ca_topic_score_gemma":0.003230995,"domain_scores_codex":[0.9988938,0.0003446996,0.00004220624,0.0003400096,0.0002855802,0.00009376706],"domain_scores_gemma":[0.9969543,0.002001501,0.0005094972,0.0001452433,0.0003129989,0.00007639227],"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":[0.00003075211,0.00002803527,0.0007603598,0.00004385503,0.00005867382,0.00008786859,0.000078757,0.9654777,0.00147922,0.02092922,0.0001902477,0.01083532],"study_design_scores_gemma":[0.000005598909,0.00001402838,0.000148346,0.000001599228,0.000005549836,0.000007348539,0.000007472025,0.9958352,0.000140255,0.003709954,0.0001204355,0.000004239095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0240283,0.0002379451,0.9745554,0.0002796775,0.00002470162,0.00001862904,0.0000152082,0.0000580644,0.0007821005],"genre_scores_gemma":[0.9664597,0.0003075784,0.03135245,0.00008743983,0.0000665178,0.0001164327,0.00004982304,0.00002024206,0.001539953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005768456,"threshold_uncertainty_score":0.01146972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03431661957130654,"score_gpt":0.2586300080740703,"score_spread":0.2243133885027638,"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."}}