{"id":"W2944947372","doi":"10.1109/cdc40024.2019.9029953","title":"Towards robustness guarantees for feedback-based optimization","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; McGill University","funders":"","keywords":"Robustness (evolution); Leverage (statistics); Computer science; Mathematical optimization; Monotone polygon; Robust optimization; Robust control; Control theory (sociology); Optimization problem; Mathematics; Control system; Control (management); Engineering; Artificial intelligence","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":[0.005234033,0.002078701,0.00121436,0.001417544,0.0004900103,0.002417432,0.001640767,0.001890423,0.003388289],"category_scores_gemma":[0.02302142,0.000559235,0.001145592,0.0008323828,0.002615292,0.002346622,0.003199579,0.002893648,0.00061622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001248409,"about_ca_system_score_gemma":0.001081193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001225032,"about_ca_topic_score_gemma":0.000488039,"domain_scores_codex":[0.9963026,0.001577229,0.0001608707,0.0004541653,0.001296752,0.0002084912],"domain_scores_gemma":[0.9865006,0.01003897,0.001133905,0.0008231706,0.001285365,0.0002180548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001243643,0.00005606436,0.0003227842,0.0003286946,0.00006785308,0.0001093623,0.0001412259,0.7431154,0.004896579,0.227286,0.001282705,0.02226907],"study_design_scores_gemma":[0.00001063204,0.0000424028,0.00006366063,0.00002917906,0.000005281909,0.00001456808,0.00001161413,0.9295949,0.0008335373,0.06874431,0.0006432103,0.000006623103],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007229174,0.00051133,0.9872652,0.0002538106,0.00003206929,0.00003627621,0.00005503343,0.0002401899,0.004376937],"genre_scores_gemma":[0.8277808,0.001352778,0.1661194,0.0003226641,0.0002365055,0.0004191791,0.0002303497,0.0004084928,0.00312984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005234033,"threshold_uncertainty_score":0.02768052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02676779179201842,"score_gpt":0.2623245127947876,"score_spread":0.2355567210027692,"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."}}