{"id":"W2078456547","doi":"10.1117/12.779348","title":"Collaborative distributed sensor management and information exchange flow control for multitarget tracking using Markov decision processes","year":2008,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Markov decision process; Computer science; Information exchange; Redundancy (engineering); Sensor fusion; Information flow; Markov process; Distributed computing; Information transfer; Partially observable Markov decision process; Real-time computing; Markov chain; Data mining; Artificial intelligence; Markov model; Machine learning","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":[0.0004219739,0.0002682421,0.0003411929,0.0001238881,0.0002319997,0.0002399933,0.0005849474,0.0001411097,0.000001884442],"category_scores_gemma":[0.0004964413,0.0002295824,0.0002343108,0.0006374541,0.0001290003,0.002009941,0.0001412327,0.0001503493,3.795491e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001326561,"about_ca_system_score_gemma":0.00003409065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002689423,"about_ca_topic_score_gemma":9.856935e-8,"domain_scores_codex":[0.9981558,2.990953e-8,0.000607101,0.0003303287,0.0005614595,0.0003452589],"domain_scores_gemma":[0.996079,0.0002311573,0.0003995546,0.00005601278,0.003120043,0.000114273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002575372,0.001154225,0.001514013,0.009085501,0.004426065,0.000003435698,0.004694067,0.04183257,0.1231162,0.7285016,0.02812875,0.05496819],"study_design_scores_gemma":[0.002677706,0.00025442,0.0008431536,0.0002689491,0.00009986557,0.00004004711,0.0008500455,0.975251,0.01118807,0.0006595719,0.007505156,0.0003620744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8111029,0.0001465211,0.1862791,0.0005734931,0.000270219,0.001057269,0.0003254207,0.00010473,0.0001404189],"genre_scores_gemma":[0.1769317,0.0003069675,0.8221511,0.000119881,0.0002132289,0.0001929066,0.00003107342,0.00002674488,0.00002639096],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9334184,"threshold_uncertainty_score":0.9362099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00969574809479207,"score_gpt":0.220522548397645,"score_spread":0.210826800302853,"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."}}