{"id":"W2327877278","doi":"10.2514/6.2012-2518","title":"An Introspective Learning Algorithm that Achieves Robust Adaptive Control of a Quadrotor Helicopter","year":2012,"lang":"en","type":"article","venue":"Infotech@Aerospace 2012","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Robust control; Adaptive control; Control (management); Introspection; Artificial intelligence; Robustness (evolution); Control theory (sociology); Control engineering; Control system; Engineering; Psychology; Electrical 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":[0.0006337804,0.0005020399,0.0007606773,0.0002081182,0.0001095389,0.0000549881,0.0003591422,0.000350407,0.0001434971],"category_scores_gemma":[0.00007943067,0.0004819587,0.0001926633,0.0002381294,0.0001564516,0.001694174,0.00005824988,0.0007434802,0.0002940276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002442405,"about_ca_system_score_gemma":0.00003151241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001165759,"about_ca_topic_score_gemma":0.00003824105,"domain_scores_codex":[0.9977196,0.0001785725,0.0004698181,0.0002952726,0.0004674169,0.0008693544],"domain_scores_gemma":[0.9984367,0.0002078089,0.000264899,0.0005180783,0.0002053202,0.000367142],"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":[0.001602846,0.002028048,0.2413144,0.0006681429,0.005096585,0.00006407379,0.02352425,0.3724288,0.2304813,0.008916873,0.005564455,0.1083103],"study_design_scores_gemma":[0.007921497,0.001919507,0.1286263,0.0004316302,0.0003630676,0.00009285366,0.00571047,0.7990937,0.02536516,0.00007622588,0.02756795,0.002831694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05410801,0.002993363,0.938255,0.00006118249,0.0009602925,0.001105758,0.0001412336,0.0008157751,0.001559417],"genre_scores_gemma":[0.9807205,0.00003120906,0.01759469,0.00003818483,0.001013387,0.0001320692,0.00001354754,0.0001371,0.0003193658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9266124,"threshold_uncertainty_score":0.9997632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01587583120166152,"score_gpt":0.2240323806974959,"score_spread":0.2081565494958344,"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."}}