{"id":"W2759716989","doi":"10.1109/iros.2018.8594283","title":"Cost Adaptation for Robust Decentralized Swarm Behaviour","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Swarm behaviour; Leverage (statistics); Distributed computing; Adaptation (eye); Task (project management); Set (abstract data type); Heuristic; Process (computing); Mathematical optimization; Artificial intelligence; Engineering; Systems engineering","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":[0.000610254,0.0004142271,0.0005195912,0.0001445564,0.0001419883,0.0007402133,0.002131201,0.0003948635,0.00004512017],"category_scores_gemma":[0.0001388032,0.0003981313,0.0003159706,0.0001625997,0.00004286017,0.000290236,0.0008212836,0.0002444831,0.0001640043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002918903,"about_ca_system_score_gemma":0.0003387909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000432151,"about_ca_topic_score_gemma":0.0001777345,"domain_scores_codex":[0.9970214,0.0001259003,0.0006742129,0.001083483,0.0004838021,0.0006112354],"domain_scores_gemma":[0.997101,0.0001410146,0.000479232,0.001409699,0.0006424371,0.000226598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005092321,0.002401617,0.005411142,0.00144557,0.001748777,0.0001001437,0.006803151,0.1938217,0.0003721592,0.2162465,0.4014719,0.1696681],"study_design_scores_gemma":[0.002114299,0.00006911961,0.0009946387,0.0001289828,0.00008366204,0.000006340921,0.00006859884,0.9826564,0.0005799267,0.001833682,0.01084275,0.0006216256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00101522,0.0001191971,0.9888164,0.0007371751,0.004379734,0.003282346,0.0002452467,0.0006591632,0.0007455128],"genre_scores_gemma":[0.4808988,0.00003274328,0.513051,0.0003483913,0.0005605182,0.002007505,0.0009942953,0.00006609086,0.002040675],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7888346,"threshold_uncertainty_score":0.9998471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1231573022020559,"score_gpt":0.3156610486183004,"score_spread":0.1925037464162445,"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."}}