{"id":"W4381730733","doi":"10.2514/1.g007715","title":"Impact Angle Control Guidance Considering Seeker’s Field-of-View Limit Based on Reinforcement Learning","year":2023,"lang":"en","type":"article","venue":"Journal of Guidance Control and Dynamics","topic":"Guidance and Control Systems","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Missile; Reinforcement learning; Computer science; Limit (mathematics); Process (computing); Acceleration; Constraint (computer-aided design); Train; Control theory (sociology); Missile guidance; Field of view; Field (mathematics); Proportional navigation; Controller (irrigation); Control (management); Artificial intelligence; Engineering; Mathematics; Aerospace engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009464979,0.0003019696,0.0008532782,0.0002671691,0.000094279,0.00006473712,0.0002175958,0.0001352605,0.00001611483],"category_scores_gemma":[0.0003793093,0.0002540644,0.0003162739,0.0002879955,0.00004108346,0.0002161638,0.00001647156,0.0004088782,0.000009581097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001565513,"about_ca_system_score_gemma":0.00009255971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002337445,"about_ca_topic_score_gemma":0.00002144372,"domain_scores_codex":[0.9977912,0.00009459442,0.001082632,0.0001669817,0.0004150079,0.0004495802],"domain_scores_gemma":[0.9981886,0.0006147478,0.0005017429,0.0002498415,0.0002724894,0.0001725396],"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":[0.0003319067,0.00002109016,0.02769381,0.0002003517,0.0002446037,0.00007299222,0.00007643292,0.9563203,0.003302241,0.0002140199,0.0007562128,0.01076601],"study_design_scores_gemma":[0.004732177,0.0009256225,0.01463148,0.0007414309,0.00008810315,0.0000367459,0.00007609345,0.976856,0.00007036413,0.0000813377,0.001510553,0.0002500744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4927262,0.01424949,0.4826348,0.001993582,0.002143437,0.001041731,0.00006297243,0.0004096795,0.004738123],"genre_scores_gemma":[0.9987113,0.000434329,0.0001616077,0.0003031173,0.0002295104,0.00001598159,0.000002988521,0.00004123736,0.00009989185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5059851,"threshold_uncertainty_score":0.9999912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00832919846041905,"score_gpt":0.2422693466458931,"score_spread":0.233940148185474,"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."}}