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Book Chapter
Stochastic Bounds for Partially Generated Markov Chains: An Algebraic Approach
Book Series
Lecture Notes in Computer Science
Publisher
Springer Berlin / Heidelberg
ISSN
0302-9743 (Print) 1611-3349 (Online)
Volume
Volume 5261/2008
Book
Computer Performance Engineering
DOI
10.1007/978-3-540-87412-6
Copyright
2008
ISBN
978-3-540-87411-9
DOI
10.1007/978-3-540-87412-6_17
Pages
227-241
Subject Collection
Computer Science
SpringerLink Date
Friday, September 26, 2008
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Stochastic Bounds for Partially Generated Markov Chains: An Algebraic Approach
Ana Bušić
1
and Jean-Michel Fourneau
1, 2
(1)
INRIA Grenoble - Rhône-Alpes, 51, Av. J. Kuntzmann, 38330 Montbonnot, France
(2)
PRiSM, Université de Versailles-St-Quentin, 45, Av. des Etats-Unis, 78035 Versailles, France
Abstract
We propose several algorithms to obtain bounds based on Censored Markov Chains to analyze partially generated discrete time Markov chains. The main idea is to avoid the generation of a huge (or even infinite) state space and to truncate the state space during the visit. The approach is purely algebraic and provides element-wise and stochastic bounds for the CMC.
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