{"id":"W1950070584","doi":"10.1007/978-3-540-78671-9_25","title":"Cooperative Problem Decomposition in Pareto Competitive Classifier Models of Coevolution","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Genetic programming; Pareto principle; Classifier (UML); Artificial intelligence; Coevolution; Modularity (biology); Population; Machine learning; Mathematical optimization; Pareto optimal; Multi-objective optimization; 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":[0.002841427,0.0008574381,0.001587241,0.0008927695,0.0008317532,0.002547141,0.002465682,0.002625275,0.004984965],"category_scores_gemma":[0.009656134,0.0007308181,0.001206786,0.001109167,0.001780782,0.003125725,0.002095775,0.002137883,0.0008302998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00152269,"about_ca_system_score_gemma":0.001268649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003510529,"about_ca_topic_score_gemma":0.002597196,"domain_scores_codex":[0.9985898,0.0007182991,0.00005119185,0.0002100552,0.0002799732,0.0001506089],"domain_scores_gemma":[0.9963114,0.002389786,0.0002087228,0.0003405878,0.0005467797,0.0002027981],"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":[0.0000862782,0.0001249021,0.0005505481,0.00009809401,0.00007030803,0.00008365968,0.0002545082,0.5408667,0.0009277798,0.412419,0.003506691,0.04101149],"study_design_scores_gemma":[0.00000658583,0.00001040578,0.00004654258,0.000005178544,0.000006440212,0.00001297483,0.00001555899,0.9333866,0.00006171885,0.06612723,0.000316476,0.000004288073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03553556,0.0005572797,0.9505979,0.0005880901,0.00006118462,0.00008116018,0.00005006614,0.00009944466,0.01242937],"genre_scores_gemma":[0.7427989,0.0007937461,0.2252203,0.000320579,0.0001767914,0.0005346239,0.0002472619,0.0001398762,0.02976786],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004984965,"threshold_uncertainty_score":0.01667643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01988100542659253,"score_gpt":0.2539309474162396,"score_spread":0.234049941989647,"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."}}