{"id":"W2139042205","doi":"10.1609/socs.v2i1.18203","title":"Faster Optimal and Suboptimal Hierarchical Search","year":2021,"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":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; National Science Foundation","keywords":"Heuristic; Incremental heuristic search; Weighting; Computer science; Beam search; Best-first search; Search algorithm; Simple (philosophy); Greedy algorithm; Local search (optimization); Function (biology); Bidirectional search; Mathematical optimization; Algorithm; Mathematics; Artificial intelligence","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":[0.002586479,0.0008205022,0.001639529,0.0008344778,0.0006176264,0.001253403,0.001415241,0.00137442,0.005798638],"category_scores_gemma":[0.01046098,0.0006402639,0.0009272228,0.001178725,0.00102638,0.002561819,0.002092501,0.001867699,0.0009144529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001604004,"about_ca_system_score_gemma":0.002567326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005021422,"about_ca_topic_score_gemma":0.008235572,"domain_scores_codex":[0.9979447,0.0007608599,0.0001019234,0.0003776792,0.0006072839,0.0002074965],"domain_scores_gemma":[0.9962483,0.002193499,0.0002071747,0.0009337894,0.0002853728,0.0001319257],"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":[0.0004521502,0.0002525139,0.001685363,0.0003407917,0.00009914763,0.00008961642,0.0003252129,0.5988805,0.005370206,0.1204312,0.01154422,0.2605291],"study_design_scores_gemma":[0.00007010884,0.00006921576,0.0002310047,0.00002092669,0.00001610012,0.00003480015,0.00003679732,0.9439478,0.001097245,0.05171361,0.00275274,0.000009647999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03538428,0.0007957616,0.9517356,0.0004166595,0.00006667123,0.0001514788,0.0001291753,0.001806481,0.009513857],"genre_scores_gemma":[0.3026683,0.0002077066,0.6925244,0.0004091619,0.00004074434,0.0002594729,0.0004578306,0.000344919,0.003087514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005798638,"threshold_uncertainty_score":0.01939839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0149486210134715,"score_gpt":0.250929431142466,"score_spread":0.2359808101289945,"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."}}