International Conference on Computational Methods in Systems Biology

CMSB 2015: Computational Methods in Systems Biology pp 15-27 | Cite as

SReach: A Probabilistic Bounded Delta-Reachability Analyzer for Stochastic Hybrid Systems

  • Qinsi Wang
  • Paolo Zuliani
  • Soonho Kong
  • Sicun Gao
  • Edmund M. Clarke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9308)

Abstract

In this paper, we present a new tool SReach, which solves probabilistic bounded reachability problems for two classes of models of stochastic hybrid systems. The first one is (nonlinear) hybrid automata with parametric uncertainty. The second one is probabilistic hybrid automata with additional randomness for both transition probabilities and variable resets. Standard approaches to reachability problems for linear hybrid systems require numerical solutions for large optimization problems, and become infeasible for systems involving both nonlinear dynamics over the reals and stochasticity. SReach encodes stochastic information by using a set of introduced random variables, and combines \(\delta \)-complete decision procedures and statistical tests to solve \(\delta \)-reachability problems in a sound manner. Compared to standard simulation-based methods, it supports non-deterministic branching, increases the coverage of simulation, and avoids the zero-crossing problem. We demonstrate SReach’s applicability by discussing three representative biological models and additional benchmarks for nonlinear hybrid systems with multiple probabilistic system parameters.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Qinsi Wang
    • 1
  • Paolo Zuliani
    • 2
  • Soonho Kong
    • 1
  • Sicun Gao
    • 3
  • Edmund M. Clarke
    • 1
  1. 1.Computer Science DepartmentCarnegie Mellon UniversityPittsburghUSA
  2. 2.School of Computing ScienceNewcastle UniversityNewcastle upon TyneUK
  3. 3.CSAILMassachusetts Institute of TechnologyCambridgeUSA

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