{"id":"W3033502170","doi":"10.1007/978-3-030-44625-3_3","title":"Equilibria of Parametrized N-Player Nonlinear Games Using Inequalities and Nonsmooth Dynamics","year":2020,"lang":"en","type":"book-chapter","venue":"Springer optimization and its applications","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Nash equilibrium; Mathematical economics; Variational inequality; Nonlinear system; Mathematics; Best response; Mathematical optimization; Applied mathematics; Game theory; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005723045,0.000316175,0.0006048646,0.000393497,0.0002176013,0.0001866232,0.0003987646,0.0002579256,0.0003977664],"category_scores_gemma":[0.0002865872,0.0002922489,0.0001076403,0.0003528973,0.0002806058,0.0002118604,0.0002904501,0.0002406615,0.00003775975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003208882,"about_ca_system_score_gemma":0.000106363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004131211,"about_ca_topic_score_gemma":0.000004393455,"domain_scores_codex":[0.9975591,0.00004970134,0.001003042,0.0007136618,0.0005090251,0.0001654454],"domain_scores_gemma":[0.9972713,0.000677326,0.0007822016,0.0005960514,0.0004816454,0.0001914619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002071451,0.00002831683,0.00002461208,0.00004886121,0.0000484481,2.874066e-7,0.0001723318,0.008218518,0.0002784459,0.987111,0.00007344029,0.003975041],"study_design_scores_gemma":[0.0004607132,0.00004580979,0.00001547661,0.00007850699,0.0001831904,0.000009525073,0.000261028,0.8259369,0.0001889027,0.0860743,0.08620344,0.0005422739],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002294917,0.002216834,0.8974163,0.002205426,0.00009887069,0.002291465,0.001406588,0.0001715325,0.09189808],"genre_scores_gemma":[0.2602529,0.009514351,0.4151066,0.001432393,0.0009674975,0.0006054396,0.001354863,0.0005468459,0.3102192],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9010367,"threshold_uncertainty_score":0.999953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1079216443579259,"score_gpt":0.3442337184688434,"score_spread":0.2363120741109175,"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."}}