{"id":"W2553081833","doi":"10.1007/s10458-016-9350-8","title":"A novel abstraction for swarm intelligence: particle field optimization","year":2016,"lang":"en","type":"article","venue":"Autonomous Agents and Multi-Agent Systems","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Particle swarm optimization; Multi-swarm optimization; Abstraction; Swarm intelligence; Swarm behaviour; Computer science; Perspective (graphical); Metaheuristic; Field (mathematics); Set (abstract data type); Heuristic; Mathematical optimization; Artificial intelligence; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005395287,0.0001542735,0.0001863679,0.00009214629,0.0001966048,0.0002767459,0.000339618,0.00008618154,0.00004170506],"category_scores_gemma":[0.0002344259,0.0001111744,0.00005281851,0.0001563365,0.00003014366,0.0004303228,0.0001188321,0.00005435518,0.00004443478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008798652,"about_ca_system_score_gemma":0.00006257659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001150391,"about_ca_topic_score_gemma":0.000003541407,"domain_scores_codex":[0.9984362,0.00005266346,0.0004411816,0.0004735299,0.0002555691,0.0003409056],"domain_scores_gemma":[0.9988038,0.0002539635,0.0001708056,0.0003795588,0.0002071703,0.0001847358],"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":[0.00007322287,0.001332583,0.001396267,0.0003573272,0.0002908079,0.00002265098,0.00207584,0.4944169,0.007013871,0.03014608,0.003442894,0.4594316],"study_design_scores_gemma":[0.0006764248,0.00009926391,0.0003431835,0.00003818888,0.000009003967,0.00001548572,0.0000491666,0.9906934,0.002261379,0.00001479996,0.005632829,0.0001668474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001326494,0.00009646617,0.9956675,0.0008272551,0.000976307,0.0008763601,0.00001608585,0.0001215933,0.0000919353],"genre_scores_gemma":[0.7109598,0.0002312789,0.2829171,0.0001853819,0.0001352442,0.000311159,0.000008025463,0.00002635293,0.005225733],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7127504,"threshold_uncertainty_score":0.4533562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07563508047408636,"score_gpt":0.3298468779985365,"score_spread":0.2542117975244502,"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."}}