{"id":"W2120198850","doi":"10.1109/icassp.2007.366756","title":"On Optimality of Monotone Channel-Aware Transmission Policies: A Constrained Markov Decision Process Approach","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Markov decision process; Computer science; Lagrange multiplier; Markov process; Fading; Mathematical optimization; Network packet; Transmission (telecommunications); Channel (broadcasting); Channel state information; Constraint (computer-aided design); Buffer overflow; Transmission delay; Wireless; Computer network; Mathematics; Telecommunications; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005865297,0.001635954,0.002579141,0.001430111,0.0009096807,0.001781942,0.001575802,0.002033907,0.005095697],"category_scores_gemma":[0.01912881,0.001218957,0.001677584,0.001127259,0.003067364,0.003014504,0.002192119,0.003032491,0.0004475044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003332523,"about_ca_system_score_gemma":0.0056578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009742317,"about_ca_topic_score_gemma":0.005024395,"domain_scores_codex":[0.9970202,0.001447069,0.0001015294,0.0003852738,0.0005363877,0.0005095261],"domain_scores_gemma":[0.980442,0.01692624,0.0008844146,0.00033763,0.00101908,0.0003906375],"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":[0.00006496967,0.00005098827,0.0002417268,0.00008002533,0.00004045705,0.00008219972,0.00006024894,0.8682495,0.0005512758,0.1258866,0.0007067308,0.003985235],"study_design_scores_gemma":[0.00001783779,0.00001845343,0.0000434846,0.00001413227,0.000005616808,0.000009591679,0.000005400632,0.9616388,0.0001268219,0.03795584,0.0001570129,0.000006969861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01393503,0.0003414254,0.9792439,0.0008335114,0.00004007265,0.00008838761,0.0001430422,0.00008136112,0.005293328],"genre_scores_gemma":[0.7694345,0.001740026,0.220948,0.0006388631,0.0002188589,0.0007697694,0.0003985745,0.000211576,0.00563995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009742317,"threshold_uncertainty_score":0.03101897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008190102650428192,"score_gpt":0.2542238095223014,"score_spread":0.2460337068718733,"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."}}