{"id":"W3136757919","doi":"10.1609/aaai.v35i14.17469","title":"Policy-Guided Heuristic Search with Guarantees","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Compute Canada; Canadian Institute for Advanced Research","keywords":"Incremental heuristic search; Beam search; Heuristic; Best-first search; Computer science; Mathematical optimization; Function (biology); Bidirectional search; Search algorithm; Quality (philosophy); Search cost; Null-move heuristic; Algorithm; Artificial intelligence; Mathematics; Economics","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":[0.002955753,0.001298074,0.001413314,0.0008330295,0.0006578884,0.001587856,0.001589854,0.002036947,0.00377483],"category_scores_gemma":[0.01860971,0.0006742297,0.0007969714,0.0009266011,0.001961401,0.002478914,0.002220885,0.002829471,0.0008684451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001819818,"about_ca_system_score_gemma":0.004504014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00326961,"about_ca_topic_score_gemma":0.003106479,"domain_scores_codex":[0.9977284,0.00083802,0.0001340901,0.0003247611,0.0006678125,0.0003069525],"domain_scores_gemma":[0.9890106,0.007901855,0.000733691,0.001310965,0.0007146278,0.0003283025],"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":[0.0001927192,0.00009877487,0.0007272753,0.0001289689,0.0000407825,0.0000603877,0.0000861032,0.8800415,0.001538788,0.06883226,0.002355249,0.04589716],"study_design_scores_gemma":[0.00003939656,0.00004467764,0.00005535566,0.00001633208,0.000006438303,0.00001934583,0.00001237098,0.973224,0.0005146245,0.02525321,0.000808684,0.000005603438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0319722,0.0004535727,0.9557055,0.0007064784,0.00007399683,0.0001127136,0.00009189131,0.001318815,0.009564936],"genre_scores_gemma":[0.6772691,0.0005350187,0.3162452,0.0004447511,0.00008081519,0.0003590771,0.0002864115,0.0003333867,0.00444623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00377483,"threshold_uncertainty_score":0.01563168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09946954893367661,"score_gpt":0.3333868331638339,"score_spread":0.2339172842301573,"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."}}