{"id":"W7124303883","doi":"10.65109/sjjn3653","title":"Is Nash Equilibrium Approximator Learnable?","year":2023,"lang":"","type":"article","venue":"","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Learnability; Nash equilibrium; Generalization; Function (biology); Upper and lower bounds; Probably approximately correct learning","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004620316,0.0003280918,0.0004670376,0.0004643712,0.0005097234,0.0009003067,0.002071613,0.0002271507,0.05154698],"category_scores_gemma":[0.001009407,0.0002638076,0.0003487128,0.005806886,0.0004859837,0.0006426719,0.0009749643,0.0003326063,0.2193946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002923738,"about_ca_system_score_gemma":0.0002258631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001604914,"about_ca_topic_score_gemma":0.000002387198,"domain_scores_codex":[0.9949544,0.0002838056,0.001080937,0.001213807,0.001552505,0.0009145658],"domain_scores_gemma":[0.9954106,0.001660953,0.0002625546,0.00190563,0.0003145442,0.0004457635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000485925,0.0002098214,0.001255234,0.00003255067,0.00005657418,0.00001496021,0.002573526,0.0001882138,0.009808602,0.2685651,0.6692416,0.04800519],"study_design_scores_gemma":[0.0004109103,0.00007930765,0.001595178,0.00002436387,0.00002986083,0.00001177723,0.006374292,0.03047564,0.0118006,0.3749831,0.5737274,0.0004875172],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5390022,0.0002172654,0.005320217,0.0309952,0.001271187,0.0008961895,0.0001195381,0.0008010148,0.4213772],"genre_scores_gemma":[0.6024477,0.00004985,0.0003995093,0.001148796,0.000169911,0.00004962746,0.000004980847,0.00002550544,0.3957041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1678476,"threshold_uncertainty_score":0.9999814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1740320059506578,"score_gpt":0.4127392377308282,"score_spread":0.2387072317801704,"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."}}