{"id":"W4282968580","doi":"10.48550/arxiv.2206.06492","title":"On Strategic Measures and Optimality Properties in Discrete-Time Stochastic Control with Universally Measurable Policies","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Alberta Innovates - Technology Futures; DeepMind; Alberta Machine Intelligence Institute","keywords":"Markov decision process; Mathematics; Minimax; Axiom; Optimal control; Mathematical economics; Determinacy; Stochastic control; Variety (cybernetics); Discrete time and continuous time; Class (philosophy); Mathematical optimization; Control (management); Time horizon; Action (physics); Markov process; Economics; Computer science; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007455676,0.001217023,0.00144347,0.001527894,0.0007928745,0.002811978,0.001260106,0.001823052,0.00186675],"category_scores_gemma":[0.02599127,0.0007242789,0.001358288,0.001496908,0.006857378,0.005808466,0.002475432,0.002985478,0.0002000768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002982541,"about_ca_system_score_gemma":0.002276286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002455551,"about_ca_topic_score_gemma":0.001125389,"domain_scores_codex":[0.9958718,0.001985903,0.0002427991,0.0005736013,0.000955402,0.0003704914],"domain_scores_gemma":[0.9770749,0.01828365,0.001992888,0.0007679719,0.001258482,0.0006220626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002022105,0.00002492182,0.0003721346,0.0000719981,0.00003015081,0.00004173102,0.00008879334,0.04881706,0.0005361983,0.9461735,0.0002511387,0.003572117],"study_design_scores_gemma":[0.00001681554,0.00005328888,0.0003901606,0.00003665576,0.00001200743,0.00001926296,0.00003913785,0.1487684,0.0003234732,0.8498892,0.0004356531,0.000015914],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1077717,0.002101321,0.8679967,0.003315159,0.0001037629,0.00007248849,0.0001637328,0.0001029305,0.01837227],"genre_scores_gemma":[0.9424322,0.001874977,0.05200154,0.0004078984,0.0002359333,0.0001951497,0.0001826149,0.00008296289,0.002586805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007455676,"threshold_uncertainty_score":0.03942984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09967698464418984,"score_gpt":0.1604092558841318,"score_spread":0.06073227123994196,"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."}}