Conditional steady-state bounds for a subset of states in Markov chains
Date
2006-10
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SMCtools'06: Proceeding from the 2006 Workshop on Tools for Solving Structured Markov Chains
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ACM
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English
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Abstract
The problem of computing bounds on the conditional steady-state probability vector of a subset of states in finite, ergodic discrete-time Markov chains (DTMCs) is considered. An improved algorithm utilizing the strong stochastic (st-)order is given. On standard benchmarks from the literature and other examples, it is shown that the proposed algorithm performs better than the existing one in the strong stochastic sense. Furthermore, in certain cases the conditional steady-state probability vector of the subset under consideration can be obtained exactly. Copyright 2006 ACM.
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Keywords
Bounding, Conditional steady-state vector, Markov chains, Stochastic comparison, Strong stochastic order, Computing bounds, Conditionla steady state probability vectors, Discrete time markov chains, Stochastic comparisons, Algorithms, Probability distributions, Stochastic control systems, Vectors, Markov processes