IJPAM: Volume 59, No. 2 (2010)

OPTIMAL THRESHOLD PROBABILITY AND POLICY
ITERATION IN SEMI-MARKOV DECISION PROCESSES

Masahiko Sakaguchi$^1$, Yoshio Ohtsubo$^2$
$^1$Graduate School of Integrated Arts and Sciences
Kochi University
2-5-1, Akebono-cho, Kochi, 780-8520, JAPAN
$^2$Department of Mathematics
Faculty of Science
Kochi University
2-5-1, Akebono-cho, Kochi, 780-8520, JAPAN
e-mail: ohtsubo@kochi-u.ac.jp


Abstract.We consider undiscounted semi-Markov decision process with a target set and our main concern is a problem minimizing threshold probability. We formulate the problem as an infinite horizon case with a recurrent class. We show that an optimal value function is a unique solution to an optimality equation and there exists a stationary optimal policy. Also several value iteration methods and a policy improvement method are given in our model.

Received: January 29, 2010

AMS Subject Classification: 90C40, 90C31

Key Words and Phrases: semi-Markov decision process, optimal threshold probability, existence of optimal policy, value iteration, policy improvement method

Source: International Journal of Pure and Applied Mathematics
ISSN: 1311-8080
Year: 2010
Volume: 59
Issue: 2