{"id":"W4312270764","doi":"10.1109/access.2022.3227076","title":"A Secure Decentralized Event-Triggered Cooperative Localization in Multi-Robot Systems Under Cyber Attack","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Robot; Mobile robot; Bounded function; Denial-of-service attack; Event (particle physics); Convergence (economics); Distributed computing; Resilience (materials science); Vulnerability (computing); Computer network; Real-time computing; Computer security; Artificial intelligence; The Internet; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007420804,0.000309224,0.000492566,0.0002593035,0.0003984817,0.000774891,0.002112797,0.0001023914,0.00007714221],"category_scores_gemma":[0.00006381154,0.0003099978,0.0001027145,0.001701866,0.00003665343,0.001254308,0.0004490287,0.0003749999,0.00005704872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006691156,"about_ca_system_score_gemma":0.0002423382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008353292,"about_ca_topic_score_gemma":0.0003223053,"domain_scores_codex":[0.9959021,0.001219574,0.0007575175,0.0007751246,0.0007347218,0.0006109318],"domain_scores_gemma":[0.9983814,0.0001549745,0.0003404704,0.0007355791,0.0002300414,0.0001575388],"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":[0.00003942533,0.0003631037,0.002754823,0.00003991303,0.00007281295,0.00008425153,0.000979388,0.9879705,0.0006378961,0.001944756,0.004796633,0.0003164652],"study_design_scores_gemma":[0.004449486,0.00004796251,0.001584586,0.00007634592,0.00001494178,0.00002136786,0.0003392609,0.9878277,0.0004248181,0.00004485367,0.004729856,0.000438857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02156834,0.0008458354,0.9721978,0.0004566367,0.002995591,0.00152122,0.00007670916,0.0002336719,0.0001041746],"genre_scores_gemma":[0.9981151,0.0000200578,0.0002161248,0.0006005856,0.0000548417,0.0006014887,0.00006160564,0.000029929,0.0003002415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9765468,"threshold_uncertainty_score":0.9999352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06925134915125818,"score_gpt":0.3405940039052651,"score_spread":0.2713426547540069,"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."}}