{"id":"W3211042025","doi":"10.1109/cdc45484.2021.9683724","title":"Deep Structured Teams in Arbitrary-Size Linear Networks: Decentralized Estimation, Optimal Control and Separation Principle","year":2021,"lang":"en","type":"article","venue":"2021 60th IEEE Conference on Decision and Control (CDC)","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Kalman filter; Curse of dimensionality; Mathematical optimization; Computer science; Optimal control; Linear system; Mathematics; Linear-quadratic-Gaussian control; Separation principle; Deep learning; Control theory (sociology); Nonlinear system; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007142014,0.0004915575,0.0009109241,0.000166084,0.0002333586,0.0008962177,0.0005824655,0.0003034942,0.0001234148],"category_scores_gemma":[0.0006886118,0.000451382,0.0001280814,0.0005558283,0.00009673178,0.0007000474,0.0001071415,0.0004362597,0.00003422791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001117655,"about_ca_system_score_gemma":0.0003641285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003414427,"about_ca_topic_score_gemma":0.0001947804,"domain_scores_codex":[0.9959313,0.0005201275,0.001009397,0.001175611,0.0006785222,0.0006850284],"domain_scores_gemma":[0.9968261,0.001075407,0.0003471151,0.0008519056,0.0004861646,0.0004133283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0031525,0.0008690738,0.008951406,0.00009127214,0.0005269489,0.0009555989,0.001164868,0.3378877,0.01306235,0.115223,0.0008423624,0.5172729],"study_design_scores_gemma":[0.01383779,0.0001498351,0.01498722,0.0001572723,0.00004371732,0.00005271035,0.00006693754,0.9675575,0.000234438,0.00169136,0.0007776174,0.0004435469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07823552,0.001109899,0.9175817,0.001106706,0.0007678702,0.0008901369,0.00003812384,0.00009252886,0.0001775007],"genre_scores_gemma":[0.9850403,0.0003133205,0.0132695,0.0009792462,0.00011359,0.0001079472,0.00003160893,0.00002306592,0.0001214158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9068048,"threshold_uncertainty_score":0.9997938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01232964050328096,"score_gpt":0.2837180941247158,"score_spread":0.2713884536214349,"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."}}