{"id":"W7133116061","doi":"","title":"Empirical Models of Heuristic Search in AI Planning and Neural Sequence Decoding","year":2021,"lang":"","type":"dissertation","venue":"TSpace","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Beam search; Heuristic; Incremental heuristic search; Decoding methods; Search algorithm; Satisficing; Empirical research; Sequence (biology)","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":[0.007040329,0.001102119,0.001335466,0.001671403,0.0008210431,0.002743836,0.002307168,0.002243883,0.005189575],"category_scores_gemma":[0.0822682,0.001191479,0.001102274,0.001765441,0.003930227,0.00750986,0.001993725,0.004037566,0.0007439357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003283623,"about_ca_system_score_gemma":0.002562481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005795995,"about_ca_topic_score_gemma":0.006332548,"domain_scores_codex":[0.9956434,0.002133358,0.0002288862,0.0008451538,0.0007945537,0.0003548182],"domain_scores_gemma":[0.9407272,0.04826949,0.003895398,0.004238058,0.002254304,0.0006156029],"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":[0.0001262895,0.0001080304,0.004661308,0.00019297,0.00009862899,0.00008045796,0.0004122733,0.7264406,0.0009213793,0.2425282,0.002029798,0.0224],"study_design_scores_gemma":[0.0000168521,0.00004299016,0.0007247329,0.00003335769,0.000009522883,0.0000391465,0.00005403737,0.8797932,0.0003795738,0.1184015,0.0004869647,0.00001816262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1386461,0.001121024,0.8448195,0.002649989,0.00005291601,0.0001626793,0.0004755906,0.0006472727,0.01142493],"genre_scores_gemma":[0.8345317,0.0009064479,0.1584106,0.0005347273,0.00006270604,0.0005518695,0.0007528831,0.000335387,0.003913811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007040329,"threshold_uncertainty_score":0.03723323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1220743046594857,"score_gpt":0.4282263411095157,"score_spread":0.30615203645003,"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."}}