{"id":"W4404332156","doi":"10.1016/b978-0-443-14081-5.00085-4","title":"Learning in Multi-Agent Games Over Networks","year":2024,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","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":[0.0005813834,0.0008111758,0.0006638084,0.0003439516,0.0003462724,0.001827081,0.0007962711,0.001072163,0.008787274],"category_scores_gemma":[0.002262911,0.0003534019,0.0003520972,0.0007137239,0.001048707,0.002121316,0.0008111947,0.002059208,0.001065115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009828302,"about_ca_system_score_gemma":0.0005436308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002248457,"about_ca_topic_score_gemma":0.002111792,"domain_scores_codex":[0.9997106,0.0001208434,0.0000140628,0.000042487,0.0000838936,0.00002807973],"domain_scores_gemma":[0.9989241,0.0008931375,0.00004068049,0.00004272941,0.00004823262,0.00005109502],"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":[0.00004992825,0.0001013697,0.0002900287,0.0002916749,0.00004297333,0.00009854796,0.0002051817,0.2135213,0.000803165,0.6414805,0.01936086,0.1237544],"study_design_scores_gemma":[0.00002819966,0.00002871556,0.0001813678,0.00006505096,0.000009383204,0.00004814077,0.00004841513,0.4088853,0.0002567935,0.5628705,0.02756676,0.00001138142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01828357,0.01080104,0.7411817,0.004053439,0.0007780397,0.00009369646,0.0001745316,0.0004485941,0.2241854],"genre_scores_gemma":[0.5820934,0.01675908,0.1471942,0.0007292129,0.00154656,0.0004671712,0.0004307596,0.0002046036,0.2505748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008787274,"threshold_uncertainty_score":0.02939636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893613279638714,"score_gpt":0.2466580939506332,"score_spread":0.227721961154246,"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."}}