{"id":"W4387385672","doi":"10.1109/access.2023.3322193","title":"Data-Efficient MADDPG Based on Self-Attention for IoT Energy Management Systems","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Reinforcement learning; Computer science; Scalability; Exploit; Dependency (UML); Distributed computing; Artificial intelligence; Machine learning; Computer security; Database","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":[0.0003407703,0.0002141393,0.0001776586,0.0003969195,0.00009020743,0.0001865413,0.0009198937,0.00005729591,0.00001107466],"category_scores_gemma":[0.000004938523,0.0002190098,0.0000576666,0.0005687451,0.000008369807,0.0001054255,0.0001744148,0.00005356238,0.00009468471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001556322,"about_ca_system_score_gemma":0.000007377275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004252937,"about_ca_topic_score_gemma":0.0000190405,"domain_scores_codex":[0.9984832,0.00002523711,0.0002785291,0.000433126,0.0003674173,0.0004125097],"domain_scores_gemma":[0.9987696,0.00007363725,0.00004386866,0.001013899,0.00003005762,0.00006887042],"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":[0.000008262829,0.00004605145,0.0000420234,0.0003674048,0.0001143921,0.00001757429,0.000004266238,0.8964524,0.00005067071,0.002031598,0.09949725,0.001368111],"study_design_scores_gemma":[0.0004624474,0.00001843899,0.001223083,0.00006320349,0.00005696766,2.970957e-7,0.00001564013,0.8544108,0.0002763992,0.00001793368,0.143243,0.000211719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06533992,0.0001306338,0.8792917,0.0003292761,0.02285417,0.001815473,0.0003858564,0.006505688,0.02334727],"genre_scores_gemma":[0.9961568,0.00005071479,0.0005699256,0.0001547113,0.0005727044,0.0007807681,0.0005669276,0.0001076866,0.001039746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9308169,"threshold_uncertainty_score":0.893096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04216583175407556,"score_gpt":0.2760929926559682,"score_spread":0.2339271609018926,"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."}}