{"id":"W4226079167","doi":"10.4230/lipics.cp.2022.35","title":"Decision Diagrams for Discrete Optimization: A Survey of Recent Advances","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Agencia Nacional de Investigación y Desarrollo","keywords":"Computer science; Integer programming; Discrete optimization; Influence diagram; Key (lock); Point (geometry); Constraint programming; Constraint (computer-aided design); Mathematical optimization; Optimization problem; Diagram; Theoretical computer science; Management science; Operations research; Algorithm; Artificial intelligence; Stochastic programming; Mathematics; Decision tree; Engineering","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":[0.00564154,0.002186934,0.00239174,0.003704285,0.0007300117,0.004286687,0.003076431,0.001825551,0.01018533],"category_scores_gemma":[0.01339334,0.001586084,0.002289887,0.008921383,0.002244641,0.005808447,0.002537035,0.005460186,0.002941628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002928735,"about_ca_system_score_gemma":0.003034058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003727859,"about_ca_topic_score_gemma":0.002554882,"domain_scores_codex":[0.9953693,0.001697415,0.000375358,0.0006121934,0.001784746,0.0001610662],"domain_scores_gemma":[0.9889764,0.008907197,0.0003392084,0.0006136188,0.0009318261,0.000231855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000899716,0.000127567,0.0005168747,0.004888766,0.0001379699,0.00008026744,0.0001973118,0.04164864,0.0006067008,0.4160461,0.01658918,0.5190707],"study_design_scores_gemma":[0.00006847086,0.0001122685,0.0003854079,0.002250578,0.00009880918,0.0003175538,0.0001420807,0.1066175,0.001106101,0.4548291,0.4339817,0.00009052534],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.001583685,0.3679947,0.6063375,0.002859037,0.0007963017,0.00009525153,0.0002777065,0.0005479555,0.01950786],"genre_scores_gemma":[0.05887266,0.5088641,0.4192388,0.001485646,0.002854667,0.0003316918,0.001063942,0.0007333325,0.006555108],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01018533,"threshold_uncertainty_score":0.03407335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08826301017131544,"score_gpt":0.2326968505489794,"score_spread":0.144433840377664,"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."}}