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Stochastic Bounds for Partially Generated Markov Chains: An Algebraic Approach

  • Ana Bušić
  • Jean-Michel Fourneau
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5261)

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.

Keywords

Markov Chain Transition Probability Matrix Stochastic Matrix Discrete Time Markov Chain Positive Matrice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ana Bušić
    • 1
  • Jean-Michel Fourneau
    • 1
    • 2
  1. 1.INRIA Grenoble - Rhône-AlpesMontbonnotFrance
  2. 2.PRiSM, Université de Versailles-St-QuentinVersaillesFrance

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