{"id":"W2808541151","doi":"10.24963/ijcai.2018/669","title":"Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models","year":2018,"lang":"en","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Leverage (statistics); Computer science; Automated planning and scheduling; Exploit; Artificial intelligence; Plan (archaeology); Discretization; Curse of dimensionality; Theoretical computer science; Constraint (computer-aided design); Mathematical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002276563,0.0001110794,0.0001202366,0.00008058076,0.0001501779,0.0001828593,0.000116084,0.00004218028,0.000004898574],"category_scores_gemma":[0.000002639483,0.00008725984,0.00001151471,0.0002653029,0.00003425587,0.0007895381,0.00002505531,0.0001349058,0.000002898719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001642969,"about_ca_system_score_gemma":0.00002589621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002433093,"about_ca_topic_score_gemma":0.0001020829,"domain_scores_codex":[0.9991459,0.00007831144,0.0001176748,0.0002734902,0.0001236526,0.0002609259],"domain_scores_gemma":[0.9996713,0.00006079357,0.00005223752,0.0001292636,0.00003019966,0.00005623889],"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":[0.0003653923,0.00002289268,0.007710626,0.0000217647,0.00001910115,0.00003423911,0.02115171,0.950494,0.0009256555,0.000733251,0.0003847547,0.01813659],"study_design_scores_gemma":[0.0005667484,0.0003151956,0.002828311,0.00007184008,0.000002734414,0.00001192653,0.0001728949,0.9927135,0.0002653125,0.002869508,0.00003876829,0.0001433012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4924801,0.00003455682,0.5065122,0.0004934475,0.00005010002,0.00006269756,3.700549e-7,0.00008317435,0.000283404],"genre_scores_gemma":[0.9744137,0.000004831089,0.02522248,0.0001609203,0.00004245119,0.000003890575,0.000003417007,0.000006454752,0.0001418375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4819337,"threshold_uncertainty_score":0.3558353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05009573217793577,"score_gpt":0.2693127140951196,"score_spread":0.2192169819171838,"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."}}