Previous |  Up |  Next

Article

Title: Solutions of semi-Markov control models with recursive discount rates and approximation by $\epsilon$-optimal policies (English)
Author: García, Yofre H.
Author: González-Hernández, Juan
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 55
Issue: 3
Year: 2019
Pages: 495-517
Summary lang: English
.
Category: math
.
Summary: This paper studies a class of discrete-time discounted semi-Markov control model on Borel spaces. We assume possibly unbounded costs and a non-stationary exponential form in the discount factor which depends of on a rate, called the discount rate. Given an initial discount rate the evolution in next steps depends on both the previous discount rate and the sojourn time of the system at the current state. The new results provided here are the existence and the approximation of optimal policies for this class of discounted Markov control model with non-stationary rates and the horizon is finite or infinite. Under regularity condition on sojourn time distributions and measurable selector conditions, we show the validity of the dynamic programming algorithm for the finite horizon case. By the convergence in finite steps to the value functions, we guarantee the existence of non-stationary optimal policies for the infinite horizon case and we approximate them using non-stationary $\epsilon$-optimal policies. We illustrated our results a discounted semi-Markov linear-quadratic model, when the evolution of the discount rate follows an appropriate type of stochastic differential equation. (English)
Keyword: optimal stochastic control
Keyword: dynamic programming method
Keyword: semi-Markov processes
MSC: 49L20
MSC: 93E20
idZBL: Zbl 07144950
idMR: MR4015995
DOI: 10.14736/kyb-2019-3-0495
.
Date available: 2019-11-14T08:37:06Z
Last updated: 2023-08-22
Stable URL: http://hdl.handle.net/10338.dmlcz/147862
.
Reference: [1] Arnold, L.: Stochastic Differential Equations..John Wiley and Sons, New York 1973. MR 0443083
Reference: [2] Ash, R., Doléans-Dade, C.: Probability and Measure Theory..Academic Press, San Diego, 2000. Zbl 0944.60004, MR 1810041
Reference: [3] Bhattacharya, R., Majumdar, M.: Controlled semi-Markov models - the discounted case..J. Statist. Plann. Inference 21 (1989), 3, 365-381. MR 0995606, 10.1016/0378-3758(89)90053-0
Reference: [4] Bertsekas, D., Shreve, S.: Stochastic Optimal Control: The Discrete Time Case..Athena Scientific, Belmont, Massachusetts 1996. Zbl 0633.93001, MR 0809588
Reference: [5] Blackwell, D.: Discounted dynamic programming..Ann. Math. Statist. 36, (1965), 226-235. MR 0173536, 10.1214/aoms/1177700285
Reference: [6] Cani, J. De: A dynamic programming algorithm for embedded Markov chains the planning horizon is infinitely..Management. Sci. 10 (1963), 716-733. MR 0169690, 10.1287/mnsc.10.4.716
Reference: [7] Drenyovszki, R., Kovács, L., Tornai, K., Oláh, A., I., I. Pintér: Bottom-up modeling of domestic appliances with Markov chains and semi-Markov processes..Kybernetika 53 (2017), 6, 1100-1117. 10.14736/kyb-2017-6-1100
Reference: [8] Dekker, R., Hordijk, A.: Denumerable semi-Markov decision chains with small interest rates..Ann. Oper. Res. 28 (1991), 185-212. MR 1105173, 10.1007/bf02055581
Reference: [9] García, Y., González-Hernández, J.: Discrete-time Markov control process with recursive discounted rates..Kybernetika 52 (2016), 403-426. MR 3532514, 10.14736/kyb-2016-3-0403
Reference: [10] González-Hernández, J., López-Martínez, R., Pérez-Hernández, J.: Markov control processes with randomized discounted cost..Math. Meth. Oper. Res. 65 (2006), 27-44. Zbl 1126.90075, MR 2302022, 10.1007/s00186-006-0092-2
Reference: [11] González-Hernández, J., Villarreal-Rodríguez, C.: Optimal solutions of constrained discounted semi-Markov control problems.
Reference: [12] Hernández-Lerma, O., Lasserre, J.: Discrete-Time Markov Control Processes. Basic Optimality Criteria..Springer-Verlag, New York 1996. Zbl 0840.93001, MR 1363487, 10.1007/978-1-4612-0729-0_1
Reference: [13] Hu, Q., Yue, W.: Markov Decision Processes With Their Applications..Springer-Verlag, Advances in Mechanics and Mathematics book series 14, (2008). MR 2361223, 10.14736/kyb-2017-1-0059
Reference: [14] Huang, X., Huang, Y.: Mean-variance optimality for semi-Markov decision processes under first passage criteria..Kybernetika 53 (2017), 1, 59-81. MR 3638556, 10.14736/kyb-2017-1-0059
Reference: [15] Howard, R.: Semi-Markovian decision processes..Bull. Int. Statist. Inst. 40 (1963), 2, 625-652. MR 0173545
Reference: [16] Jewell, W.: Markov-renewal programming I: formulation, finite return models, Markov-renewal programming II: infinite return models, example..Oper. Res. 11 (1963), 938-971. MR 0163375, 10.1287/opre.11.6.938
Reference: [17] Luque-Vázquez, F., Hernández-Lerma, O.: Semi-Markov control models with average costs..Appl. Math. 26 (1999), 315-331. MR 1726636, 10.4064/am-26-3-315-331
Reference: [18] Luque-Vásquez, F., Minjárez-Sosa, J. A.: Semi-Markov control processes with unknown holding times distribution under a discounted criterion..Math. Methods Oper. Res. 61 (2005), 455-468. MR 2225824, 10.1007/s001860400406
Reference: [19] Luque-Vásquez, F., Minjárez-Sosa, J., Rosas, L.: Semi-Markov control processes with unknown holding times distribution under an average cost criterion..Appl. Math. Optim. 61, (2010), 317-336. MR 2609593, 10.1007/s00245-009-9086-9
Reference: [20] Schweitzer, P.: Perturbation Theory and Markovian Decision Processes..Ph.D. Dissertation, Massachusetts Institute of Technology, 1965. MR 2939613
Reference: [21] Vasicek, O.: An equilibrium characterization of the term structure..J. Financ. Econom. 5 (1977), 177-188. 10.1016/0304-405x(77)90016-2
Reference: [22] Vega-Amaya, O.: Average optimatily in semi-Markov control models on Borel spaces: unbounded costs and control..Bol. Soc. Mat. Mexicana 38 (1997), 2, 47-60. MR 1313106
Reference: [23] Zagst, R.: The effect of information in separable Bayesian semi-Markov control models and its application to investment planning..ZOR - Math. Methods Oper. Res. 41 (1995), 277-288. MR 1339493, 10.1007/BF01432360
.

Files

Files Size Format View
Kybernetika_55-2019-3_4.pdf 480.1Kb application/pdf View/Open
Back to standard record
Partner of
EuDML logo