Approximate Solutions to Semi Markov Decision Processes through Markov Chain Montecarlo Methods

摘要

We explore the possibilities of Markov Chain Monte Carlo simulation methods to solve sequential decision processes evolving stochastically in time. The application areas of such processes are fairly wide, embedded typically in the Decision Analysis framework, such as preventive maintenance of systems, where we shall find our illustrative examples.