{"id":"W4313120064","doi":"10.1609/socs.v1i1.18159","title":"Bootstrap Learning of Heuristic Functions","year":2010,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristic; Bootstrapping (finance); Null-move heuristic; Incremental heuristic search; Consistent heuristic; Computer science; Process (computing); Mathematical optimization; Algorithm; Sequence (biology); Mathematics; Artificial intelligence; Beam search; Search algorithm; Econometrics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003272354,0.001463986,0.001563718,0.001705768,0.0006196671,0.001289877,0.002159918,0.001585472,0.005147683],"category_scores_gemma":[0.0232305,0.0007945381,0.001097639,0.001169062,0.001698548,0.002054289,0.002010361,0.00208401,0.001224626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001253134,"about_ca_system_score_gemma":0.001471432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0012355,"about_ca_topic_score_gemma":0.00192454,"domain_scores_codex":[0.9980063,0.001030192,0.0001015601,0.0003055399,0.0004239417,0.0001324597],"domain_scores_gemma":[0.9910199,0.00621273,0.0004732641,0.001389012,0.0006824306,0.0002226121],"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":[0.000262231,0.000305282,0.002741499,0.0004534071,0.0001844524,0.0001436128,0.0001991734,0.731966,0.002064235,0.05885555,0.006097069,0.1967275],"study_design_scores_gemma":[0.00004945914,0.00008362223,0.0001241446,0.0000415278,0.00001867949,0.00002634924,0.00002934904,0.9587823,0.001025558,0.0379797,0.001829938,0.000009323401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03227827,0.0006648437,0.9546613,0.0004484833,0.000113137,0.0002733607,0.0001817833,0.001804639,0.009574174],"genre_scores_gemma":[0.5740529,0.0004561882,0.4196971,0.0004750486,0.0001239673,0.0007831785,0.0008701461,0.0003020893,0.003239225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005147683,"threshold_uncertainty_score":0.01730609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01505893033952621,"score_gpt":0.2562940177736008,"score_spread":0.2412350874340746,"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."}}