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An ant system approach to Markov decision processes

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4 Author(s)
Hyeong Soo Chang ; Dept. of Comput. Sci. & Eng., Sogang Univ., Seoul, South Korea ; Gutjahr, W.J. ; Jihoon Yang ; Sungyong Park

In this paper, we develop an ant-system based algorithm for approximately solving large Markov decision process (MDP) problems for infinite horizon discounted cost criterion, extending the applicability of the ant-system meta-heuristic into stochastic sequential decision making problems. The algorithm inherits the spirit of the well-known policy iteration algorithm with an adaptation of the ant system into MDP settings with some modifications and extensions, while preserving the probabilistic convergence property of the ant system.

Published in:

American Control Conference, 2004. Proceedings of the 2004  (Volume:4 )

Date of Conference:

June 30 2004-July 2 2004