{"id":"W123800271","doi":"10.1609/aaai.v25i1.7880","title":"Automated Action Abstraction of Imperfect Information Extensive-Form Games","year":2011,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Perfect information; Limit (mathematics); Action (physics); Computer science; Bayesian game; Imperfect; Extensive-form game; Mathematical economics; Nash equilibrium; Space (punctuation); Focus (optics); Repeated game; Game theory; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00061067,0.00027181,0.0003265133,0.0003168243,0.0001781611,0.0001510581,0.001692466,0.0001656775,0.0001203859],"category_scores_gemma":[0.0006648166,0.0002120103,0.0001796289,0.0008731397,0.0003838098,0.002606844,0.0002775639,0.0003239183,0.0002139628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000781566,"about_ca_system_score_gemma":0.0001287921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003005746,"about_ca_topic_score_gemma":0.00001984039,"domain_scores_codex":[0.997547,0.0000230791,0.001077662,0.0003594565,0.0006276161,0.0003652383],"domain_scores_gemma":[0.9965112,0.0001006978,0.00114453,0.0004199452,0.001735271,0.00008841052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001708583,0.0002300233,0.0004049405,0.00009585414,0.00003491574,3.829406e-7,0.008830587,0.00009264259,0.09711944,0.6203004,0.0002510846,0.2724688],"study_design_scores_gemma":[0.00001494009,0.0002752227,0.002150075,0.0001498791,0.00001502332,0.000008317332,0.001823833,0.08755025,0.8302398,0.07752258,0.00005483539,0.0001952532],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9110953,0.00001907756,0.05459486,0.0008550934,0.001731018,0.0009832509,0.00001013797,0.00072746,0.02998376],"genre_scores_gemma":[0.9955989,0.00005508744,0.004122212,0.00009646025,0.00003902599,0.00002734611,8.16026e-7,0.00001085614,0.00004933477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7331203,"threshold_uncertainty_score":0.864553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1084992298471176,"score_gpt":0.3142262882419854,"score_spread":0.2057270583948678,"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."}}