ON GRADUAL-IMPULSE CONTROL OF CONTINUOUS-TIME MARKOV DECISION PROCESSES WITH EXPONENTIAL UTILITY

Guo, Xin, Kurushima, Aiko, Piunovskiy, Alexey and Zhang, Yi ORCID: 0000-0002-3200-6306 (2021) ON GRADUAL-IMPULSE CONTROL OF CONTINUOUS-TIME MARKOV DECISION PROCESSES WITH EXPONENTIAL UTILITY. ADVANCES IN APPLIED PROBABILITY, 53 (2). pp. 301-334.

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Official URL: http://dx.doi.org/10.1017/apr.2020.64

Abstract

<jats:title>Abstract</jats:title><jats:p>We consider a gradual-impulse control problem of continuous-time Markov decision processes, where the system performance is measured by the expectation of the exponential utility of the total cost. We show, under natural conditions on the system primitives, the existence of a deterministic stationary optimal policy out of a more general class of policies that allow multiple simultaneous impulses, randomized selection of impulses with random effects, and accumulation of jumps. After characterizing the value function using the optimality equation, we reduce the gradual-impulse control problem to an equivalent simple discrete-time Markov decision process, whose action space is the union of the sets of gradual and impulsive actions.</jats:p>

Item Type:	Article
Uncontrolled Keywords:	Continuous-time Markov decision processes, dynamic programming, gradual-impulse control, optimality equation
Depositing User:	Symplectic Admin
Date Deposited:	14 Sep 2020 08:41
Last Modified:	18 Jan 2023 23:33
DOI:	10.1017/apr.2020.64
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3100817