Computing least fixed points of probabilistic systems of polynomials

Javier Esparza, Andreas Gaiser, Stefan Kiefer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

We study systems of equations of the form X1 = f 1(X1,⋯, Xn),⋯, Xn = fn(X1,⋯, Xn) where each fi is a polynomial with nonnegative coefficients that add up to 1. The least nonnegative solution, say μ, of such equation systems is central to problems from various areas, like physics, biology, computational linguistics and probabilistic program verification. We give a simple and strongly polynomial algorithm to decide whether μ = (1,⋯, 1) holds. Furthermore, we present an algorithm that computes reliable sequences of lower and upper bounds on μ, converging linearly to μ. Our algorithm has these features despite using inexact arithmetic for efficiency. We report on experiments that show the performance of our algorithms.

Original languageEnglish
Title of host publicationSTACS 2010 - 27th International Symposium on Theoretical Aspects of Computer Science
Pages359-370
Number of pages12
DOIs
StatePublished - 2010
Event27th International Symposium on Theoretical Aspects of Computer Science, STACS 2010 - Nancy, France
Duration: 4 Mar 20106 Mar 2010

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume5
ISSN (Print)1868-8969

Conference

Conference27th International Symposium on Theoretical Aspects of Computer Science, STACS 2010
Country/TerritoryFrance
CityNancy
Period4/03/106/03/10

Keywords

  • Branching processes
  • Computing fixed points
  • Numerical approximation
  • Stochastic models

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