{"id":"W4396531266","doi":"10.22215/etd/2023-15915","title":"Decentralized Resource Allocation in 5G Networks with Heterogeneous Multi-Agent Reinforcement Learning","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reinforcement learning; Resource allocation; Computer science; Distributed computing; Reinforcement; Artificial intelligence; Computer network; Psychology; Social psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001097662,0.0005104129,0.0006750494,0.000181433,0.0003440426,0.0005810662,0.0006963259,0.0005627769,0.000751287],"category_scores_gemma":[0.001892631,0.0002515568,0.0003388357,0.0001904324,0.0006631077,0.0005855073,0.0007250444,0.0006807513,0.0001076197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008478618,"about_ca_system_score_gemma":0.001000151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004418091,"about_ca_topic_score_gemma":0.003569046,"domain_scores_codex":[0.9995447,0.0001993,0.00001433581,0.00008022341,0.00008099708,0.00008045394],"domain_scores_gemma":[0.999301,0.0003898275,0.00009900293,0.00004707065,0.0001151086,0.00004810637],"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":[0.00002287246,0.00002059728,0.0002716384,0.00001330727,0.00001382917,0.00002734809,0.00001526232,0.9872246,0.0005858263,0.003662906,0.0001961036,0.007945692],"study_design_scores_gemma":[0.000004587971,0.000009678118,0.00003369031,9.521881e-7,0.000001615732,0.000002534547,0.000002608233,0.9988036,0.000101464,0.000941028,0.00009710573,0.000001044445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04681276,0.0002221259,0.9497082,0.0002526885,0.00003865257,0.00004988965,0.00001964575,0.0001588055,0.002737288],"genre_scores_gemma":[0.9571987,0.0001036513,0.04096588,0.00008843307,0.00002470235,0.00006362807,0.00002136872,0.00001701046,0.001516664],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.004418091,"threshold_uncertainty_score":0.008784771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087733915232403,"score_gpt":0.2382205266027985,"score_spread":0.2273431874504745,"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."}}