{"id":"W2114871659","doi":"10.1109/tac.2004.825639","title":"Local Control Strategies for Groups of Mobile Autonomous Agents","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":859,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Convergence (economics); Focus (optics); Control (management); Computer science; Mathematical optimization; Mobile robot; Point (geometry); Autonomous agent; Control theory (sociology); Distributed computing; Mathematics; Artificial intelligence; Economics","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":[0.0005797617,0.0006856321,0.0003907698,0.0004403825,0.0003957493,0.001111618,0.0009326804,0.0006345324,0.001672414],"category_scores_gemma":[0.001766989,0.0001712729,0.0002534684,0.0003059749,0.001147868,0.0007723214,0.001121903,0.0005513321,0.0003472246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008311805,"about_ca_system_score_gemma":0.0004243742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002496861,"about_ca_topic_score_gemma":0.001743051,"domain_scores_codex":[0.9996941,0.00009286022,0.0000140711,0.00005934932,0.00009021006,0.00004946494],"domain_scores_gemma":[0.9994656,0.0002536864,0.0001014775,0.00003630596,0.0000892212,0.00005359783],"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":[0.0001351326,0.00008912079,0.000613572,0.00019066,0.00005555484,0.0003349117,0.0007327929,0.6959161,0.008745503,0.2187402,0.001873854,0.0725726],"study_design_scores_gemma":[0.00005236683,0.0001511278,0.000151259,0.00001589761,0.00001610232,0.00004025091,0.0001173385,0.9190264,0.001097874,0.07721581,0.002104838,0.00001083689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07803018,0.00123516,0.9059486,0.0004868086,0.00006660617,0.00007681721,0.00002742086,0.0002510959,0.01387739],"genre_scores_gemma":[0.9675274,0.000471071,0.02423491,0.00006968505,0.00003494614,0.00017281,0.00003436749,0.00002348017,0.007431353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002496861,"threshold_uncertainty_score":0.006030738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01522188186033223,"score_gpt":0.2627341175685133,"score_spread":0.2475122357081811,"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."}}