{"id":"W2115567587","doi":"10.1109/icsmc.2009.5345932","title":"An experimental adaptive fuzzy controller for differential games","year":2009,"lang":"en","type":"article","venue":"","topic":"Guidance and Control Systems","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Differential game; Robot; Reinforcement learning; Controller (irrigation); Computer science; Pursuer; Fuzzy logic; Markov decision process; Control theory (sociology); Position (finance); Fuzzy control system; Markov process; Control engineering; Artificial intelligence; Control (management); Engineering; Mathematics; Mathematical optimization","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006779248,0.0003567762,0.0003769256,0.0002622758,0.0003883129,0.0005338674,0.001086331,0.0006266396,0.003835625],"category_scores_gemma":[0.001798995,0.0001259245,0.0002360527,0.0001193909,0.0004587714,0.0004242306,0.0006191369,0.0006855387,0.0002220801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006710348,"about_ca_system_score_gemma":0.0005663813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003032245,"about_ca_topic_score_gemma":0.001828405,"domain_scores_codex":[0.9996983,0.00005488174,0.00001670685,0.00005482461,0.0001399423,0.00003542323],"domain_scores_gemma":[0.9994255,0.0002387407,0.00004973714,0.00006778864,0.0001593312,0.00005904245],"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":[0.001423304,0.001465136,0.001927754,0.0006620439,0.0001146639,0.0007719878,0.0004296464,0.6371368,0.1422108,0.06164773,0.002714033,0.1494961],"study_design_scores_gemma":[0.00007192555,0.000361153,0.0002448375,0.000006882977,0.000007296446,0.00003000821,0.00001290241,0.986378,0.009291205,0.002132554,0.001452064,0.0000111909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2242618,0.0002356943,0.7554879,0.0003698382,0.0003987735,0.0006498507,0.0001261491,0.001323898,0.01714606],"genre_scores_gemma":[0.9399973,0.00005074092,0.05598206,0.00006172193,0.000009232151,0.0002399238,0.00003887144,0.00001385967,0.003606466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003835625,"threshold_uncertainty_score":0.01283145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0103548773746992,"score_gpt":0.2338103247866714,"score_spread":0.2234554474119722,"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."}}