Abstract
The basic concept of learning control systems is introduced. Synthesis of learning control systems using statistical decision theory is discussed. Learning is needed if the a priori information is unknovn or incompletely known in an adaptive system. The controller will establish the necessary information for control during the system’s operation. Two types of learning, with external supervision and without external supervision, have been described. Several learning schemes, including both parametric and nonparametric approaches, have been proposed. Problems of possible computational difficulties and the convergence of learning processes are also discussed.
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Fu, K.S. (1966). A Class of Learning Control Systems Using Statistical Decision Processes. In: Hammond, P.H. (eds) Theory of Self-Adaptive Control Systems. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-6289-8_1
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DOI: https://doi.org/10.1007/978-1-4899-6289-8_1
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