{"id":"W2050550668","doi":"10.1007/s11269-006-9143-y","title":"A Fuzzy Stochastic Dynamic Nash Game Analysis of Policies for Managing Water Allocation in a Reservoir System","year":2007,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Water resources management and optimization","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Nash equilibrium; Stochastic programming; Fuzzy logic; Dynamic programming; Mathematical optimization; Sequential game; Operator (biology); Operations research; Game theory; Engineering; Mathematics; Mathematical economics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002413163,0.000802147,0.001278894,0.0009621186,0.0006867638,0.001962749,0.001657798,0.001291005,0.003736845],"category_scores_gemma":[0.004652769,0.0005805246,0.0008787455,0.0006790594,0.001469915,0.001804288,0.001013531,0.0008992806,0.0001460932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003542961,"about_ca_system_score_gemma":0.003005645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02887221,"about_ca_topic_score_gemma":0.01470933,"domain_scores_codex":[0.9991702,0.000375646,0.00002435478,0.00009689664,0.0001899208,0.000143148],"domain_scores_gemma":[0.9983622,0.001097614,0.000122353,0.00003701843,0.0002663558,0.000114361],"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":[0.00003103061,0.00002051409,0.000149781,0.00001916177,0.00002025092,0.00003270192,0.00002677346,0.9630834,0.0004873176,0.03395499,0.0002661665,0.001907903],"study_design_scores_gemma":[0.000003532438,0.000008649833,0.00003244292,0.000001453362,0.00000421382,0.000002852423,0.000007436476,0.9965194,0.00004203655,0.003306552,0.00006815986,0.000003152976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1014378,0.0003054305,0.8801671,0.0007267277,0.00008779747,0.0001368745,0.0001187674,0.0001257662,0.01689375],"genre_scores_gemma":[0.9679242,0.0001880242,0.02643577,0.00007997602,0.0000349012,0.00007134397,0.00004272129,0.0000349364,0.005188177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02887221,"threshold_uncertainty_score":0.05740833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007265319918982517,"score_gpt":0.2142090367669017,"score_spread":0.2069437168479192,"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."}}