{"id":"W4408780256","doi":"10.1109/tccn.2025.3554003","title":"QoE-Guaranteed Optimization in MEC-Enabled Metaverse: An Active Inference Deep Reinforcement Learning Approach","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Cognitive Communications and Networking","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Reinforcement learning; Computer science; Inference; Artificial intelligence; Computer network","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":[0.001140239,0.0009206338,0.001381465,0.0003957385,0.000340066,0.0009840112,0.001686887,0.001466218,0.00228979],"category_scores_gemma":[0.00292812,0.0004864584,0.0004324942,0.0003598116,0.0009171143,0.001124233,0.001141329,0.001615556,0.0002383173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00110276,"about_ca_system_score_gemma":0.001425398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008369179,"about_ca_topic_score_gemma":0.007160154,"domain_scores_codex":[0.999581,0.0001051453,0.00001547351,0.0001023099,0.00007863298,0.0001174206],"domain_scores_gemma":[0.9983581,0.001091369,0.0001336914,0.00006130763,0.0002518633,0.0001036923],"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":[0.00008232054,0.000061953,0.0007761305,0.00003640231,0.00002924293,0.00006699707,0.00002760842,0.977509,0.0007504014,0.003875931,0.0005476158,0.0162364],"study_design_scores_gemma":[0.000004114779,0.00001007996,0.00003682529,0.000002072096,0.00000258254,0.000003869653,0.000002413104,0.9989176,0.00007238994,0.000897533,0.00004922438,0.000001416957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05685796,0.0006365834,0.9367092,0.0006361828,0.00006917999,0.00004939467,0.00008272973,0.0004324802,0.004526299],"genre_scores_gemma":[0.9711128,0.0001268475,0.02613196,0.0002008691,0.00003547894,0.0000510145,0.00006338706,0.00003821356,0.002239516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008369179,"threshold_uncertainty_score":0.0166409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05062850571869744,"score_gpt":0.3321089659858775,"score_spread":0.2814804602671801,"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."}}