{"id":"W1700100050","doi":"10.5555/1402383.1402435","title":"Sequential decision making in repeated coalition formation under uncertainty","year":2008,"lang":"en","type":"article","venue":"ePrints Soton (University of Southampton)","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Reinforcement learning; Computer science; Variety (cybernetics); Bayesian probability; Artificial intelligence; Machine learning; Mathematical optimization; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008268805,0.0006416891,0.001321299,0.0007790932,0.0008599423,0.002294852,0.001232609,0.001498661,0.007475134],"category_scores_gemma":[0.01595453,0.0006621387,0.0007325571,0.001300166,0.00250756,0.002643577,0.001991754,0.001630553,0.000556902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00263627,"about_ca_system_score_gemma":0.002402126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00401012,"about_ca_topic_score_gemma":0.004473525,"domain_scores_codex":[0.9952325,0.00299424,0.0002208137,0.0005618359,0.0005698596,0.0004208113],"domain_scores_gemma":[0.9873224,0.01006743,0.001081322,0.0004419053,0.0005874611,0.0004996093],"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":[0.0003784521,0.0001267251,0.001184647,0.0002074265,0.0002092766,0.0002943274,0.0004260846,0.4193071,0.0007257454,0.5452262,0.001733762,0.03018029],"study_design_scores_gemma":[0.00008959287,0.00008698308,0.0002977599,0.00002343003,0.00002497127,0.00002593696,0.0001100327,0.4327624,0.0002195456,0.5648106,0.001528605,0.00002006729],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2003578,0.001574352,0.747323,0.003453568,0.0001860437,0.0003725029,0.0002834191,0.000139372,0.04630998],"genre_scores_gemma":[0.9341792,0.0006712087,0.05290966,0.0001069901,0.00008547479,0.0002936732,0.0001260042,0.00002411194,0.01160359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008268805,"threshold_uncertainty_score":0.04373014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1092218318883699,"score_gpt":0.33186663062423,"score_spread":0.2226447987358601,"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."}}