连续时间马尔可夫决策过程中最优控制的存在性

M. Yasuda
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引用次数: 3

摘要

本文研究连续时间马尔可夫决策过程的最优控制问题,该决策过程具有随时间和状态变化的Borel状态空间和紧致作用空间。我们在这里考虑的代价函数是在有限范围内的收益率积分的和,这取决于控制器和相应的响应,以及系统在最终固定时间的期望收益。我们的最优控制问题是在给定的规划范围内找到一个使成本函数最大的控制器。主要结果是最优性的充分必要条件,以及寻找最优控制器的算法。B. L. Miller[1]处理的问题与我们的类似,但他的论文仅限于有限状态空间和动作空间的情况。由于K. Tsuji和N. Furukawa[3]的隐函数引理,我们的情况得以成功。本文算法的构造方法常用于动态规划问题,如文献[4]。
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ON THE EXISTENCE OF OPTIMAL CONTROL IN CONTINUOUS TIME MARKOV DECISION PROCESSES
In this paper we shall treat the optimal control problem in continuous time Markov decision processes having a Borel state space and a compact action space varying with both the time and the state. The cost functional we consider here is the sum of the integral over the finite horizon of a return rate which depends on both the controller and the corresponding response, and the expected return of the system at the final fixed time. Our optimal control problem is to find a controller which maximzie the cost functional over the given planning horizon. Main results are a necessary and sufficient condition for an optimality, and an algorithm for finding the optimal controller. B. L. Miller [1] treated the problem similar to ours, but his paper was restricted to the case of the finite state space and action space. Our situation is succeeded owing to the implicit function's lemma of K. Tsuji and N. Furukawa [3]. The method of construction of our algorithm is often used in Dynamic Programming problem, for example in [4].
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