{"id":"W87408738","doi":"","title":"Apprentissage de la coordination multiagent : Q-learning par jeu adaptatif","year":2005,"lang":"fr","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Humanities; Nash equilibrium; Mathematical economics; Philosophy; Mathematics","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":[0.001368949,0.0002871358,0.0002236,0.0001340293,0.0003600046,0.0007385741,0.0007011499,0.0002363332,0.001351577],"category_scores_gemma":[0.0004397207,0.0003223015,0.0001280963,0.0004113209,0.0002044918,0.00106117,0.000381864,0.0007033596,0.001173062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002856478,"about_ca_system_score_gemma":0.0001565463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001311064,"about_ca_topic_score_gemma":0.00001372967,"domain_scores_codex":[0.9970364,0.0007490393,0.0004797661,0.0004875589,0.0005283192,0.0007189016],"domain_scores_gemma":[0.9983377,0.0005890098,0.0002493212,0.0004401809,0.0001442908,0.0002394855],"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":[0.000002969231,0.00007940474,0.001687477,0.00003724158,0.00003547818,0.00002258467,0.003188642,0.7678071,0.000337902,0.0419544,0.005538755,0.179308],"study_design_scores_gemma":[0.0004128,0.00008806245,0.002845154,0.00006913016,0.00002368328,0.00003168339,0.0001865268,0.6816096,0.000872403,0.00006184528,0.3135513,0.0002477842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002952629,0.0008543996,0.9253612,0.005107867,0.0007715938,0.0002315144,5.444565e-7,0.0003077622,0.06441247],"genre_scores_gemma":[0.6353641,0.0001422446,0.2097614,0.0002313941,0.0002591589,0.00001158824,0.000006432342,0.00002536655,0.1541983],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7155998,"threshold_uncertainty_score":0.9999229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02170017316396445,"score_gpt":0.274899334009066,"score_spread":0.2531991608451016,"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."}}