Policy Gradient Based Semi-Markov Decision Problems: Approximation and Estimation Errors-Reference-Cited by-同舟云学术

Policy Gradient Based Semi-Markov Decision Problems: Approximation and Estimation Errors

Published:2010 Issue:2 Volume:E93-D Page:271-279
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

VIEN Ngo Anh¹,LEE SeungGwan¹,CHUNG TaeChoong¹

Affiliation:

1. Artificial Intelligence Laboratory, Department of Computer Engineering, Kyung Hee University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

http://www.jstage.jst.go.jp/article/transinf/E93.D/2/E93.D_2_271/_pdf

Reference11 articles.

1. [1] N.A. Vien and T. Chung, “Policy gradient semi-Markov decision process,” 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2008), vol.2, pp.11-18, Dayton, Ohio, USA, Nov. 2008.

2. [2] N.A. Vien, N.H. Viet, S. Lee, and T. Chung, “Policy gradient SMDP for resource allocation and routing in integrated services networks,” IEICE Trans. Commun., vol.E92-B, no.6, pp.2008-2022, June 2009.

3. [3] S.M. Ross, Applied Probability Models with Optimization Applications, Holden-Day, San Francisco, 1970.

4. [4] D.P. Bertsekas, Dynamic Programming and Optimal Control, Athena Scientific, Belmont, Mass, 2001.

5. [5] M.L. Puterman, Markov Decision Processes: Discrete Stochastic Dynamic Programming, John Wiley & Sons, New Jersey, 2005.

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