Abstract
We begin in Section 2.2 by giving conditions under which υ* satisfies the Dynamic Programming Equation (Theorem 2.2), and in Section 2.3 we relate asymptotic discount optimality to a function that measures the “discrepancy” between an optimal action in state x and any other action α ∈ A(x). (Recall that A(x) denotes the set of admissible controls in state x; see Section 1.2.)
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© 1989 Springer-Verlag Berlin Heidelberg
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Hernández-Lerma, O. (1989). Discounted Reward Criterion. In: Adaptive Markov Control Processes. Applied Mathematical Sciences, vol 79. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8714-3_2
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DOI: https://doi.org/10.1007/978-1-4419-8714-3_2
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-6454-5
Online ISBN: 978-1-4419-8714-3
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