{"id":"W2177060007","doi":"10.1609/icaps.v21i1.13467","title":"Closing the Gap: Improved Bounds on Optimal POMDP Solutions","year":2011,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Automated Planning and Scheduling","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology; University of Waterloo","funders":"","keywords":"Upper and lower bounds; Sawtooth wave; Benchmark (surveying); Partially observable Markov decision process; Mathematical optimization; Bellman equation; Function (biology); Interpolation (computer graphics); Computer science; Grid; Linear programming; Mathematics; Markov decision process; Markov process; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005364034,0.0001359457,0.0001123335,0.0001253541,0.0004215252,0.0004037057,0.001137248,0.00006184784,0.0000161575],"category_scores_gemma":[0.0001833976,0.00008615715,0.00005162337,0.0001996898,0.0001126195,0.0003298883,0.0003029769,0.0003057543,0.000004783108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003097682,"about_ca_system_score_gemma":0.00006888214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002599469,"about_ca_topic_score_gemma":5.203372e-7,"domain_scores_codex":[0.9988815,0.00001498325,0.0002460893,0.0002675651,0.0003596199,0.0002302613],"domain_scores_gemma":[0.9991587,0.00006344059,0.0002164844,0.0001244658,0.0003793386,0.0000575308],"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":[0.00008717289,0.0001221933,0.001813766,0.00002284386,0.00009960067,0.000001590701,0.006357534,0.004511103,0.01823592,0.9666668,0.0003932395,0.001688233],"study_design_scores_gemma":[0.0002254031,0.000100671,0.001422966,0.0002712935,0.000005753807,0.00001637485,0.0004709312,0.9887826,0.005495477,0.003039347,0.00005808795,0.0001111159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8598687,0.00008353071,0.02306521,0.01093824,0.001109044,0.0005159429,0.0000129479,0.0009956917,0.1034107],"genre_scores_gemma":[0.9783106,0.00001327038,0.02109747,0.0003544672,0.00002590747,0.00001232078,0.000001377859,0.000007765836,0.0001767685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9842715,"threshold_uncertainty_score":0.3892944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1126074389154537,"score_gpt":0.3014754091728054,"score_spread":0.1888679702573517,"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."}}