{"id":"W2740257287","doi":"10.24963/ijcai.2017/606","title":"Numeric Planning via Abstraction and Policy Guided Search","year":2017,"lang":"en","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristics; Planner; Computer science; Abstraction; Plan (archaeology); Representation (politics); Automated planning and scheduling; Domain (mathematical analysis); Set (abstract data type); Rotation formalisms in three dimensions; Theoretical computer science; Algorithm; Artificial intelligence; Programming language; Mathematics","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":[0.001382802,0.000909653,0.0007031213,0.0009682355,0.0006772094,0.00127236,0.001377056,0.0009147836,0.003167824],"category_scores_gemma":[0.005611276,0.0005442623,0.001073834,0.001262002,0.002727485,0.002165606,0.002585318,0.001666697,0.0005951648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001570198,"about_ca_system_score_gemma":0.002354549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006250742,"about_ca_topic_score_gemma":0.006166978,"domain_scores_codex":[0.9985144,0.0005377518,0.0001081059,0.0002321239,0.0004717787,0.0001360171],"domain_scores_gemma":[0.9984945,0.0008228499,0.0001609142,0.0003586291,0.0001048977,0.00005820845],"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":[0.0001435668,0.00005153437,0.0006454818,0.0002476648,0.00004922192,0.0001528319,0.0002566196,0.7045379,0.003918753,0.1799919,0.002936082,0.1070684],"study_design_scores_gemma":[0.00003236583,0.00003740274,0.0001334956,0.00004540764,0.00001792371,0.00005785028,0.00003967375,0.8308957,0.002046345,0.1610524,0.005625478,0.00001591965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009233803,0.0003430026,0.9831729,0.0002765677,0.00003658548,0.00008487207,0.00009662643,0.001478589,0.005277147],"genre_scores_gemma":[0.2959597,0.00060189,0.7001855,0.0001579138,0.00004175332,0.0002907174,0.0003851071,0.0002105649,0.002166848],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006250742,"threshold_uncertainty_score":0.0124287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05436194631994119,"score_gpt":0.3495995063305367,"score_spread":0.2952375600105955,"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."}}