Markov reward processes can accurately model practical systems that evolve stochastically over time. A Markov reward process consists of two elements: A Markov environment and an associated reward structure. Chapter 11 in Li's book (Constructive Computation in Stochastic Models with Applications: RG-Factorizations) provides an excellent survey on this research direction.
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Markov reward processes can accurately model practical systems that evolve stochastically over time. A Markov reward process consists of two elements: A Markov environment and an associated reward structure. Chapter 11 in Li's book (Constructive Computation in Stochastic Models with Applications: RG-Factorizations) provides an excellent survey on this research direction.
创建时间：2021-09-29 04:00
