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46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05)
Analysis and Prediction of the Long-Run Behavior of Probabilistic Sequential Programs with Recursion (Extended Abstract)
Pittsburgh, Pennsylvania, USA
October 23-October 25
ISBN: 0-7695-2468-0
ASCII Text
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Tomas Brazdil, Javier Esparza, Antonin Kucera , "Analysis and Prediction of the Long-Run Behavior of Probabilistic Sequential Programs with Recursion (Extended Abstract)," Foundations of Computer Science, IEEE Annual Symposium on, pp. 521-530, 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05), 2005.
 
 
BibTex
x
 
@article{ 10.1109/SFCS.2005.19,
author = {Tomas Brazdil and Javier Esparza and Antonin Kucera },
title = {Analysis and Prediction of the Long-Run Behavior of Probabilistic Sequential Programs with Recursion (Extended Abstract)},
journal ={Foundations of Computer Science, IEEE Annual Symposium on},
volume = {0},
year = {2005},
isbn = {0-7695-2468-0},
pages = {521-530},
doi = {http://doi.ieeecomputersociety.org/10.1109/SFCS.2005.19},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Foundations of Computer Science, IEEE Annual Symposium on
TI - Analysis and Prediction of the Long-Run Behavior of Probabilistic Sequential Programs with Recursion (Extended Abstract)
SN - 0-7695-2468-0
SP521
EP530
A1 - Tomas Brazdil,
A1 - Javier Esparza,
A1 - Antonin Kucera ,
PY - 2005
KW - null
VL - 0
JA - Foundations of Computer Science, IEEE Annual Symposium on
ER -
 
Tomas Brazdil, Masaryk University
Javier Esparza, University of Stuttgart,
Antonin Kucera, Masaryk University

We introduce a family of long-run average properties of Markov chains that are useful for purposes of performance and reliability analysis, and show that these properties can effectively be checked for a subclass of infinite-state Markov chains generated by probabilistic programs with recursive procedures. We also show how to predict these properties by analyzing finite prefixes of runs, and present an ef?cient prediction algorithm for the mentioned subclass of Markov chains.

Citation:
Tomas Brazdil, Javier Esparza, Antonin Kucera , "Analysis and Prediction of the Long-Run Behavior of Probabilistic Sequential Programs with Recursion (Extended Abstract)," focs, pp.521-530, 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05), 2005
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