{"id":"W3036749975","doi":"10.1109/jiot.2020.3003449","title":"MEC-Assisted Immersive VR Video Streaming Over Terahertz Wireless Networks: A Deep Reinforcement Learning Approach","year":2020,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":281,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China","keywords":"Computer science; Viewport; Reinforcement learning; Wireless; Rendering (computer graphics); Quality of experience; Virtual reality; Energy consumption; Wireless network; Computer network; Real-time computing; Quality of service; Artificial intelligence; Telecommunications","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":[0.00042364,0.0004931855,0.0005460573,0.0001647032,0.0001697197,0.0004047216,0.0007482501,0.0005812432,0.0009225119],"category_scores_gemma":[0.0008748661,0.0002489554,0.0002741866,0.0001655988,0.0003679398,0.0004117837,0.0005638653,0.0009206846,0.0001169222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004627901,"about_ca_system_score_gemma":0.0006479208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007606057,"about_ca_topic_score_gemma":0.005414154,"domain_scores_codex":[0.999866,0.00003169711,0.000005600536,0.00002968796,0.00003437776,0.00003261797],"domain_scores_gemma":[0.999713,0.00015789,0.00003493784,0.00001249583,0.00005913958,0.0000225023],"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":[0.00004782798,0.00004757949,0.0004574032,0.0000292361,0.00002277563,0.00004732566,0.00002591133,0.9641343,0.002453277,0.002193918,0.0004062053,0.03013418],"study_design_scores_gemma":[0.00000176426,0.000007396263,0.00002469207,8.469928e-7,0.000001673746,0.000002237105,0.000001158326,0.999599,0.0001382063,0.0001811763,0.00004105144,7.991362e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05877485,0.0005270097,0.9353123,0.0003253061,0.00004905976,0.00003856342,0.00002705139,0.000396153,0.004549754],"genre_scores_gemma":[0.9643119,0.0002138307,0.03299766,0.0001084321,0.00002315138,0.00004775569,0.00003509982,0.0000252006,0.002236997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007606057,"threshold_uncertainty_score":0.01512355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0249849491158495,"score_gpt":0.2700075432383549,"score_spread":0.2450225941225054,"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."}}