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Hybrid behaviour of Markov population models

BORTOLUSSI, LUCA
2016
  • journal article

Periodico
INFORMATION AND COMPUTATION
Abstract
We investigate the behaviour of population models, specified in stochastic Concurrent Constraint Programming (sCCP). In particular, we focus on models from which we can define a semantics both in terms of Continuous Time Markov Chains (CTMC) and in terms of Stochastic Hybrid Systems, in which some populations are approximated continuously, while others are kept discrete. We will prove the correctness of the hybrid semantics from the point of view of the limiting behaviour of a sequence of models for increasing population size. More specifically, we prove that, under suitable regularity conditions, the sequence of CTMC constructed from sCCP programs for increasing population size converges to the hybrid system constructed by means of the hybrid semantics. We investigate in particular what happens for sCCP models in which some transitions are guarded by boolean predicates or in the presence of instantaneous transitions.
DOI
10.1016/j.ic.2015.12.001
WOS
WOS:000372136400004
Archivio
http://hdl.handle.net/11368/2882796
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84959420973
http://www.sciencedirect.com/science/article/pii/S0890540115001297
Diritti
open access
license:digital rights management non definito
license:digital rights management non definito
FVG url
https://arts.units.it/request-item?handle=11368/2882796
Soggetti
  • Fluid approximation

  • Mean field

  • Stochastic concurrent...

  • Stochastic hybrid sys...

  • Stochastic process al...

  • Weak convergence

  • Information System

  • Computational Theory ...

  • Theoretical Computer ...

  • Computer Science Appl...

Web of Science© citazioni
10
Data di acquisizione
Mar 26, 2024
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