Semi-Markov decision processes with a reachable state-subset
- 1 January 1989
- journal article
- research article
- Published by Taylor & Francis in Optimization
- Vol. 20 (3) , 305-315
- https://doi.org/10.1080/02331938908843446
Abstract
We consider the problem of minimizing the long-run average expected cost per unit time in a semi-Markov decision process with arbitrary state and action space, Assuming the existence .of a Borel subset of state space called a reachable state-subset, we derive the optimality equation for the unbounded costs. The contraction property [8; 9] for the average case is used, so that the assumptions of both continuity of the one-step cost function and compactness of state and action space are excluded.Keywords
This publication has 10 references indexed in Scilit:
- Markov Decision Processes with a Borel Measurable Cost Function—The Average CaseMathematics of Operations Research, 1986
- The average-optimal adaptive control of a Markov renewal model in presence of an unknown parameterMathematische Operationsforschung und Statistik. Series Optimization, 1982
- Denumerable state semi-Markov decision processes with unbounded costs, average cost criterionStochastic Processes and their Applications, 1979
- Alternative Theoretical Frameworks for Finite Horizon Discrete-Time Stochastic Optimal ControlSIAM Journal on Control and Optimization, 1978
- The optimality equation in average cost denumerable state semi-Markov decision problems, recurrency conditions and algorithmsJournal of Applied Probability, 1978
- On Dynamic Programming with Unbounded RewardsManagement Science, 1975
- Maximal Average-Reward Policies for Semi-Markov Decision Processes With Arbitrary State and Action SpaceThe Annals of Mathematical Statistics, 1971
- An Example in Denumerable Decision ProcessesThe Annals of Mathematical Statistics, 1968
- A Solution to a Countable System of Equations Arising in Markovian Decision ProcessesThe Annals of Mathematical Statistics, 1967
- Negative Dynamic ProgrammingThe Annals of Mathematical Statistics, 1966