{"id":"W3139456296","doi":"10.1109/isc253183.2021.9562941","title":"Load Balancing and Resource Allocation in Smart Cities using Reinforcement Learning","year":2021,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Reinforcement learning; Computer science; Leverage (statistics); Distributed computing; Cloud computing; Task (project management); Resource allocation; Edge computing; Process (computing); Smart city; Artificial intelligence; Computer security; Computer network; Systems engineering; Engineering; Internet of Things","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":[0.0003862685,0.00007169205,0.00009056965,0.00006187998,0.0001341387,0.0001727989,0.0001120739,0.0000293704,0.00000271407],"category_scores_gemma":[0.00006605017,0.00007481756,0.00001556647,0.0002520984,0.00001279379,0.0002342244,0.0002960119,0.00011403,0.000003807797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009525034,"about_ca_system_score_gemma":0.0001008387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001647641,"about_ca_topic_score_gemma":0.00001464568,"domain_scores_codex":[0.9991909,0.00005133282,0.0001729915,0.0002179161,0.0001639248,0.0002029851],"domain_scores_gemma":[0.9996647,0.00006257261,0.00004035543,0.0001444092,0.00005669136,0.00003128172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002725688,0.0001010588,0.2911675,0.0003985745,0.00007879589,0.0003549703,0.06717837,0.2557367,0.04502165,0.03442245,0.004004656,0.301508],"study_design_scores_gemma":[0.0001977579,0.00001553007,0.003739397,0.00008669734,0.000001676695,0.00002831275,0.0003557943,0.9803601,0.003691662,0.0001635761,0.01122606,0.0001334564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4845611,0.0001935603,0.4997641,0.0003000448,0.0006404441,0.00004263025,2.641431e-9,0.00008372196,0.01441435],"genre_scores_gemma":[0.9762679,0.000006327549,0.02156474,0.0004297539,0.0002310406,0.000001065804,0.000001171412,0.000005316276,0.00149272],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7246234,"threshold_uncertainty_score":0.3050971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01871145825694534,"score_gpt":0.2340661191949084,"score_spread":0.215354660937963,"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."}}