{"id":"W2155110786","doi":"10.1109/icsmc.2007.4414135","title":"An improved immune Q-learning algorithm","year":2007,"lang":"en","type":"article","venue":"","topic":"Artificial Immune Systems Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Reinforcement learning; Computer science; Task (project management); Q-learning; Artificial intelligence; Set (abstract data type); Key (lock); Machine learning; Action selection; Action (physics); Artificial immune system; Instance-based learning; Algorithm; Active learning (machine learning); Engineering; Perception","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":[0.001440915,0.0005347839,0.001250984,0.0007112483,0.0004974602,0.0007087667,0.002097258,0.001446684,0.004706505],"category_scores_gemma":[0.003117629,0.0003232919,0.0005746432,0.0006994245,0.0007878784,0.000822167,0.001069815,0.001012618,0.0008907146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006803786,"about_ca_system_score_gemma":0.001553732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003566601,"about_ca_topic_score_gemma":0.00216514,"domain_scores_codex":[0.9993094,0.0001849477,0.00003802464,0.0001375596,0.000220784,0.0001092716],"domain_scores_gemma":[0.9988307,0.0004284679,0.00008472471,0.00009466943,0.0004886924,0.00007274122],"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":[0.0001834519,0.0001905439,0.001488307,0.0001131251,0.00007243775,0.0001401897,0.00009420123,0.7600539,0.003389276,0.02643045,0.005573601,0.2022705],"study_design_scores_gemma":[0.00005673257,0.00003822097,0.00009723897,0.00000448473,0.000009900428,0.00003079579,0.000003658135,0.9951989,0.0003080427,0.003008605,0.00123836,0.000005054966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01779578,0.0003233614,0.9756875,0.0003127212,0.0001438324,0.0001056668,0.00004114036,0.0004755109,0.005114355],"genre_scores_gemma":[0.4458531,0.0003081708,0.5436945,0.0006822197,0.0001487666,0.0003812342,0.0002036189,0.00008691609,0.00864145],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004706505,"threshold_uncertainty_score":0.01574481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005216335561126262,"score_gpt":0.232556334052529,"score_spread":0.2273399984914027,"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."}}