{"id":"W2090335209","doi":"10.1109/itw.2010.5593331","title":"A UCT agent for Tron: Initial investigations","year":2010,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; University of Waterloo","keywords":"Monte Carlo tree search; Computer science; Randomness; Monte Carlo method; Tree (set theory); Mathematical optimization; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004498196,0.0005866667,0.0007844787,0.0007489517,0.00128234,0.002160823,0.001690205,0.001714218,0.01051211],"category_scores_gemma":[0.02294334,0.0003456509,0.0005054012,0.0006593667,0.001888781,0.003017456,0.001555303,0.001956687,0.00100854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771302,"about_ca_system_score_gemma":0.001402126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008415985,"about_ca_topic_score_gemma":0.01149554,"domain_scores_codex":[0.9979408,0.001103965,0.00007192697,0.0001883884,0.0004468252,0.0002480244],"domain_scores_gemma":[0.990053,0.007381287,0.0002759329,0.0005850125,0.001276708,0.0004280772],"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":[0.001741326,0.002214534,0.01425526,0.001579711,0.0001820931,0.001136324,0.003010895,0.5007336,0.003506943,0.3544694,0.01577242,0.1013977],"study_design_scores_gemma":[0.0001758224,0.001048262,0.00144239,0.0002101195,0.0000395707,0.0001570693,0.001032904,0.9379514,0.001929002,0.03615478,0.01982357,0.00003507202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5485443,0.004176152,0.1318877,0.004188755,0.0003357384,0.001864659,0.0007648934,0.0008538704,0.307384],"genre_scores_gemma":[0.9333174,0.001248684,0.04927937,0.0003862089,0.0000461255,0.0004513294,0.0003345485,0.0001473389,0.01478905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01051211,"threshold_uncertainty_score":0.0351665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08130451495277091,"score_gpt":0.3469649849692685,"score_spread":0.2656604700164976,"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."}}