The exponential cost optimality for finite horizon semi-Markov decision processes

Title:

The exponential cost optimality for finite horizon semi-Markov decision processes

Creator:

Huo, Haifeng and Wen, Xian

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:785b82ff-a2c8-496e-b810-3b779d527ea5
uuid:785b82ff-a2c8-496e-b810-3b779d527ea5
doi:10.14736/kyb-2022-3-0301

Subject:

semi-Markov decision processes, exponential cost, finite horizon, optimality equation, and optimal policy

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper considers an exponential cost optimality problem for finite horizon semi-Markov decision processes (SMDPs). The objective is to calculate an optimal policy with minimal exponential costs over the full set of policies in a finite horizon. First, under the standard regular and compact-continuity conditions, we establish the optimality equation, prove that the value function is the unique solution of the optimality equation and the existence of an optimal policy by using the minimum nonnegative solution approach. Second, we establish a new value iteration algorithm to calculate both the value function and the ϵ-optimal policy. Finally, we give a computable machine maintenance system to illustrate the convergence of the algorithm.

Language:

English

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

301-319

Source:

Kybernetika | 2022 Volume:58 | Number:3

Harvested from:

CDK

Metadata only:

false