{"id":"W4388040768","doi":"10.1109/pimrc56721.2023.10293793","title":"Defeating Proactive Jammers Using Deep Reinforcement Learning for Resource-Constrained IoT Networks","year":2023,"lang":"en","type":"article","venue":"","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Jamming; Computer science; Reinforcement learning; Robustness (evolution); Internet of Things; Distributed computing; Artificial intelligence; Computer security","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":[0.0009616755,0.0005246421,0.000487015,0.0002401498,0.0002476516,0.0003874501,0.0006743029,0.0004922746,0.0005692447],"category_scores_gemma":[0.002820756,0.0002326467,0.0002313842,0.0001365545,0.0007184774,0.0006056807,0.0006502886,0.0008321258,0.00008472713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006555007,"about_ca_system_score_gemma":0.0007204277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004218585,"about_ca_topic_score_gemma":0.003984907,"domain_scores_codex":[0.999782,0.00007711074,0.00001002647,0.00003240558,0.00004625517,0.00005216161],"domain_scores_gemma":[0.998843,0.0006746173,0.0001925478,0.00006511356,0.0001589975,0.00006583225],"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":[0.00003461986,0.00003641302,0.0006803573,0.00001461456,0.0000148631,0.00002082068,0.00001774243,0.9860741,0.001246969,0.001122909,0.0001299736,0.01060667],"study_design_scores_gemma":[0.000002559762,0.00001606646,0.00005328715,0.000001011929,0.000001793738,0.000002271674,0.000001702475,0.9992458,0.0001834201,0.0004592557,0.00003175449,0.000001085189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2121797,0.0003078006,0.78351,0.0004597823,0.00004972077,0.00005276575,0.00002311188,0.0004940213,0.002923143],"genre_scores_gemma":[0.9856818,0.00004747545,0.0136711,0.00007387577,0.000007495134,0.0000196559,0.00001254732,0.000008990593,0.0004769085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004218585,"threshold_uncertainty_score":0.008388042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03230598283119347,"score_gpt":0.2686205906995834,"score_spread":0.2363146078683899,"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."}}