{"id":"W2507455848","doi":"10.1007/978-3-319-44953-1_6","title":"Multiobjective Optimization by Decision Diagrams","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; The Scarborough Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Knapsack problem; Influence diagram; Computer science; Mathematical optimization; Multi-objective optimization; Set (abstract data type); Optimization problem; Diagram; State space; State (computer science); Algorithm; Decision tree; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001299095,0.000494073,0.0004214377,0.0006847662,0.0002696822,0.0004685817,0.003284567,0.0004201976,0.0000289758],"category_scores_gemma":[0.0004471998,0.0003978158,0.0001116619,0.0006215592,0.0006136643,0.001353074,0.001045452,0.0005256679,0.00008226338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006112679,"about_ca_system_score_gemma":0.0002918866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006281631,"about_ca_topic_score_gemma":0.000007930549,"domain_scores_codex":[0.9960114,0.00006785787,0.0005692813,0.001661142,0.001111787,0.0005785697],"domain_scores_gemma":[0.996646,0.0007812349,0.0004086886,0.001605498,0.0003880773,0.0001704295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006980779,0.00001878309,0.00001140114,0.000007382836,0.000004545836,0.000006470937,0.0002205986,0.05740669,0.0001277363,0.02178636,0.00003135467,0.9203717],"study_design_scores_gemma":[0.0002933375,0.0001448584,0.00003680436,0.0003276753,0.000004375181,0.00002417081,5.817608e-8,0.8770115,0.003428174,0.1169897,0.001150476,0.0005888382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000009355679,0.000282975,0.9924383,0.0002241571,0.002497366,0.0004883578,0.000009867083,0.0002179425,0.003831637],"genre_scores_gemma":[0.005345555,0.0001029726,0.9933994,0.0004881304,0.0002546727,0.00001799838,0.000005623021,0.00003530121,0.0003503067],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9197829,"threshold_uncertainty_score":0.9998474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01541185246162005,"score_gpt":0.2713594744398823,"score_spread":0.2559476219782623,"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."}}