{"id":"W4387323508","doi":"10.48550/arxiv.2310.00435","title":"Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Impossibility; Computer science; Markov process; Agency (philosophy); Axiom; Normative; Set (abstract data type); Preference; Process (computing); Mathematical optimization; Mathematical economics; Operations research; Microeconomics; Economics; Mathematics","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":[0.007244795,0.000791762,0.001067251,0.0005953619,0.000953563,0.003164984,0.001235415,0.00130281,0.001581776],"category_scores_gemma":[0.0172683,0.0006714061,0.001141935,0.0008447925,0.002160236,0.004497291,0.002215723,0.002770872,0.0002829649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002257598,"about_ca_system_score_gemma":0.002865548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001987496,"about_ca_topic_score_gemma":0.002848122,"domain_scores_codex":[0.9943182,0.00287835,0.0003919916,0.0008853407,0.0009812977,0.0005448265],"domain_scores_gemma":[0.9844632,0.009440013,0.002503241,0.001746338,0.001146609,0.0007005949],"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":[0.0001231388,0.0001293752,0.002014558,0.000117157,0.0001453367,0.00024841,0.0004681296,0.2576021,0.00343572,0.7086756,0.000783079,0.02625754],"study_design_scores_gemma":[0.00002576809,0.00009533026,0.0005607927,0.00002507888,0.00003157627,0.00009130912,0.0001160015,0.5624964,0.001202753,0.4334281,0.001896892,0.00003004934],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06389758,0.0001142463,0.9271093,0.0009249097,0.00002881449,0.0001125783,0.00006419436,0.00008620881,0.007662183],"genre_scores_gemma":[0.8077908,0.000204815,0.1875535,0.0001410642,0.00004744791,0.0001962094,0.00007890255,0.00004728925,0.003939953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007244795,"threshold_uncertainty_score":0.03831458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2031721705717537,"score_gpt":0.2703885235653542,"score_spread":0.06721635299360049,"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."}}