{"id":"W4399426672","doi":"10.1109/jiot.2024.3411158","title":"Hybrid Deep Reinforcement Learning for Enhancing Localization and Communication Efficiency in RIS-Aided Cooperative ISAC Systems","year":2024,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Science and Technology Council","keywords":"Reinforcement learning; Computer science; Artificial intelligence; Computer architecture; Distributed computing","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":[0.000565174,0.0001139901,0.0001860458,0.0002585639,0.00006883591,0.0001325001,0.0002911668,0.00005650257,0.000004872966],"category_scores_gemma":[0.0002076539,0.0001104924,0.00003350177,0.0001274093,0.0000609442,0.0005013264,0.0000577504,0.0004935973,0.000001743126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002243833,"about_ca_system_score_gemma":0.00001610885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000028597,"about_ca_topic_score_gemma":0.00001011436,"domain_scores_codex":[0.9990517,0.00005090423,0.0005241565,0.00009524853,0.0001176122,0.0001603657],"domain_scores_gemma":[0.999334,0.0002336179,0.0001267862,0.0001628464,0.0001147595,0.00002794945],"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":[0.000009100676,0.00000599884,0.0000418414,0.0001841825,0.00003084125,0.000001594846,0.00322831,0.9841253,0.00623288,0.001341784,0.00008191229,0.004716292],"study_design_scores_gemma":[0.0001957756,0.00006921224,0.000005133458,0.001128577,0.000007172229,0.00004486347,0.0008517907,0.9309757,0.06562968,0.0005115072,0.0004810152,0.00009957102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08509031,0.007330926,0.9067355,0.00003826867,0.0002512927,0.0001830441,2.897904e-7,0.0001784848,0.0001918611],"genre_scores_gemma":[0.9957446,0.001861645,0.002242252,0.000009147096,0.00001492279,0.00002797876,0.000005018372,0.00002428354,0.00007013298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9106543,"threshold_uncertainty_score":0.450575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01104509992188933,"score_gpt":0.2535416297823284,"score_spread":0.2424965298604391,"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."}}