Showing papers on "Reinforcement learning published in 1984"
TL;DR: In this paper, the authors give an overview of stochastic optimal control theory and its applications to operational research, and their actual and potential impact on OR is discussed from a methodological point of view.
53 citations
TL;DR: The systematic study of characterization equations, curves of strategies and of evolutions and transformations of strategies during the learning task are the fundamentals of a new transformation theory of learning processes.
Abstract: The systematic study of characterization equations, curves of strategies and of evolutions and transformations of strategies during the learning task are the fundamentals of a new transformation theory of learning processes. The theory has a theoretical and practical significance, particularly, for the solving of the problem of the optimal control of the learning process, and for more perfect experimental and analytical models of these processes. The individualization of the methods and means of the operator's learning, which becomes wide-spread nowadays, makes quite actual the development of a “micro-approach” to the study of learning processes, together with the traditional “macro-approach”.