{"id":"W4234022368","doi":"10.22215/etd/2014-10580","title":"Swarm Optimization Using Agents Modeled as Distributions","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Particle swarm optimization; Multi-swarm optimization; Perspective (graphical); Metaheuristic; Computer science; Heuristic; Swarm behaviour; Mathematical optimization; Field (mathematics); Black box; Artificial intelligence; Machine learning; Mathematics","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":[0.0004975774,0.0005310818,0.0006662104,0.0003914621,0.0003457915,0.001754759,0.0008102028,0.0009064348,0.00242223],"category_scores_gemma":[0.001828893,0.0003042061,0.0005706822,0.0006899123,0.0009429852,0.00160677,0.00110199,0.0009152213,0.0005973191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007863202,"about_ca_system_score_gemma":0.0008491384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002980809,"about_ca_topic_score_gemma":0.001701024,"domain_scores_codex":[0.9996473,0.0001413297,0.00001527176,0.0000596711,0.0001099055,0.00002662761],"domain_scores_gemma":[0.999599,0.0002046251,0.00004867276,0.00005486488,0.00006583942,0.00002702846],"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":[0.00002498097,0.00002067351,0.0003766509,0.00005645603,0.00004006322,0.00006857255,0.00007536819,0.7002888,0.0009555964,0.2730325,0.001885136,0.02317516],"study_design_scores_gemma":[0.00001585564,0.00001602002,0.00008272407,0.00001253536,0.000007621207,0.00001827779,0.00001311494,0.9238806,0.0002194883,0.06942236,0.006305312,0.000006131999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01024066,0.0009741006,0.9684196,0.0006133831,0.0001476047,0.00005627126,0.00006437874,0.000174899,0.01930918],"genre_scores_gemma":[0.7038487,0.00546051,0.2465631,0.0002728966,0.0003511964,0.0003096128,0.0003086081,0.0001612341,0.04272399],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002980809,"threshold_uncertainty_score":0.008103192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04076039808083713,"score_gpt":0.3485973512389364,"score_spread":0.3078369531580993,"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."}}