{"id":"W2116834924","doi":"10.1115/dscc2014-6284","title":"A Single-Leader Servo Approach to Multi-Agent Consensus Problems","year":2014,"lang":"en","type":"article","venue":"","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Servomechanism; Control theory (sociology); Constant (computer programming); Computer science; Consensus; Multi-agent system; State (computer science); Controller (irrigation); Group (periodic table); Feature (linguistics); Scheme (mathematics); Servo; Value (mathematics); Network topology; Tracking (education); Topology (electrical circuits); Control engineering; Artificial intelligence; Mathematics; Engineering; Control (management); Algorithm; 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":[0.0004701091,0.0004446499,0.0004658416,0.0003769396,0.0003351382,0.0005462012,0.0007890419,0.0006780432,0.001451164],"category_scores_gemma":[0.0008629683,0.0001488539,0.0003703659,0.0003185497,0.0005558356,0.0009055419,0.0007437943,0.000777795,0.0002028968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004149764,"about_ca_system_score_gemma":0.0004524661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004962776,"about_ca_topic_score_gemma":0.000317457,"domain_scores_codex":[0.9995998,0.00009890832,0.00002174809,0.0001160498,0.0001409153,0.00002258237],"domain_scores_gemma":[0.999775,0.0001081079,0.00003045694,0.00002143191,0.00004857884,0.00001632074],"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":[0.00006215706,0.00009851691,0.0004886086,0.0003734499,0.00005468925,0.0002455916,0.0002924598,0.6576112,0.01275394,0.2201366,0.001830444,0.1060524],"study_design_scores_gemma":[0.00001530104,0.00007918179,0.00009272735,0.00001063939,0.000008391094,0.00004299812,0.00003048814,0.9511663,0.001456793,0.04418823,0.002900229,0.000008797741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008398933,0.0007060353,0.9855399,0.0002907617,0.00007438606,0.00003183897,0.00001442469,0.00008100375,0.004862708],"genre_scores_gemma":[0.8290763,0.001597875,0.1622072,0.0002435204,0.0002513221,0.0001903694,0.00006198287,0.00003931239,0.006332176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001451164,"threshold_uncertainty_score":0.00485462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05687863516250349,"score_gpt":0.2387252989486103,"score_spread":0.1818466637861068,"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."}}