Recognition of semantically incorrect rules: a neural-network approach
IEA/AIE '90 Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2
Machine intelligence quotient: its measurements and applications
Fuzzy Sets and Systems - Special issue: Approximate Reasoning in Words
Rule Acquiring Expert Controllers
IEEE Transactions on Knowledge and Data Engineering
Learning Optimal Robotic Tasks
IEEE Expert: Intelligent Systems and Their Applications
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The basic concept of learning control is introduced. The following five learning schemes are briefly reviewed: 1) trainable controllers using pattern classifiers, 2) reinforcement learning control systems, 3) Bayesian estimation, 4) stochastic approximation, and 5) stochastic automata models. Potential applications and problems for further research in learning control are outlined.