{"id":"W4212966073","doi":"10.5220/0010803100003116","title":"Discrete Mother Tree Optimization and Swarm Intelligence for Constraint Satisfaction Problems","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 14th International Conference on Agents and Artificial Intelligence","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Constraint satisfaction; Computer science; Constraint satisfaction problem; Swarm intelligence; Constraint satisfaction dual problem; Mathematical optimization; Tree (set theory); Constraint (computer-aided design); Constraint programming; Constraint logic programming; Artificial intelligence; Particle swarm optimization; Mathematics; Algorithm; Combinatorics; Stochastic programming","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":[0.0002104271,0.0001350342,0.0001194426,0.0000968551,0.000197042,0.0001174941,0.000220098,0.00003577899,0.000184185],"category_scores_gemma":[0.00006698481,0.0001154143,0.000041522,0.0001262855,0.0001163138,0.0001335443,0.00008554581,0.0001508581,0.000001023811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004536516,"about_ca_system_score_gemma":0.00001311391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001508792,"about_ca_topic_score_gemma":0.000004726891,"domain_scores_codex":[0.9990726,0.000006612983,0.0003210248,0.0002178391,0.0002507084,0.0001312798],"domain_scores_gemma":[0.9995493,0.00003551973,0.0001264977,0.00005307356,0.0001892944,0.00004635833],"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":[0.00005807281,0.00004342939,0.0005879615,0.00005749269,0.00005776543,1.236319e-7,0.001200678,0.7423068,0.001193576,0.1819954,0.00005991561,0.07243884],"study_design_scores_gemma":[0.00004117248,0.00008437076,0.0001237215,0.00005128239,0.00001237732,0.000005004471,0.001777331,0.9760416,0.00925372,0.01235353,0.0001220993,0.0001337789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1929032,0.0001004351,0.7905412,0.003683027,0.002421729,0.00146588,0.0002158324,0.0002156417,0.008453009],"genre_scores_gemma":[0.9889247,0.0001642739,0.01053804,0.00008391742,0.00005395519,0.0000880375,0.000006317929,0.00001770108,0.0001230289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7960215,"threshold_uncertainty_score":0.4706458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05902317409062221,"score_gpt":0.2823177968179281,"score_spread":0.2232946227273059,"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."}}