{"id":"W4411183367","doi":"10.2514/1.g008786","title":"Reinforcement-Learning-Based Continuation Strategy for Autonomous On-Orbit Assembly","year":2025,"lang":"en","type":"article","venue":"Journal of Guidance Control and Dynamics","topic":"Space Satellite Systems and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Continuation; Reinforcement learning; Orbit (dynamics); Computer science; Reinforcement; Control theory (sociology); Artificial intelligence; Aerospace engineering; Engineering; Control (management); Structural engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0004203865,0.0001478406,0.0003499481,0.0001412449,0.0000674118,0.00008298401,0.00009248089,0.00008992555,0.000002627497],"category_scores_gemma":[0.00007766802,0.0001282751,0.0001242484,0.00007926307,0.00001720282,0.0001056431,0.000003309785,0.0001822497,0.00000103267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001327095,"about_ca_system_score_gemma":0.00008369234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000656526,"about_ca_topic_score_gemma":0.00002976095,"domain_scores_codex":[0.9990596,0.00002704387,0.0005065392,0.00008944423,0.0001254422,0.0001919558],"domain_scores_gemma":[0.9991919,0.0001972819,0.0002177762,0.00009267741,0.0002415157,0.00005886644],"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":[0.0002629277,0.00001431559,0.0007962835,0.00008989815,0.0001479304,0.000004127627,0.0000195692,0.956638,0.000929588,0.006167901,0.0003956589,0.03453382],"study_design_scores_gemma":[0.004127224,0.0003902188,0.00186552,0.0001649422,0.00006463523,0.000004932477,0.00006606503,0.9859422,0.00006947691,0.0002268256,0.006961074,0.0001168215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02766858,0.00217755,0.9651534,0.0006942729,0.000636308,0.0003825384,0.000009801334,0.00005464932,0.003222927],"genre_scores_gemma":[0.9985994,0.00005592217,0.0002134281,0.0001885639,0.0001116552,0.00001721116,0.000003904361,0.00001532167,0.0007946276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9709308,"threshold_uncertainty_score":0.5230907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005433611618665516,"score_gpt":0.2297160776834781,"score_spread":0.2242824660648126,"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."}}