A General Framework for Probabilistic Characterizing Formulae

Publication: Research - peer-reviewConference article – Annual report year: 2012

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A General Framework for Probabilistic Characterizing Formulae. / Sack, Joshua; Zhang, Lijun.

In: Lecture Notes in Computer Science, Vol. 7148, 2012, p. 396-411.

Publication: Research - peer-reviewConference article – Annual report year: 2012

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Author

Sack, Joshua; Zhang, Lijun / A General Framework for Probabilistic Characterizing Formulae.

In: Lecture Notes in Computer Science, Vol. 7148, 2012, p. 396-411.

Publication: Research - peer-reviewConference article – Annual report year: 2012

Bibtex

@article{6f13d9f789ec4bc5ba0d9fe2ae169c5b,
title = "A General Framework for Probabilistic Characterizing Formulae",
publisher = "Springer",
author = "Joshua Sack and Lijun Zhang",
year = "2012",
doi = "10.1007/978-3-642-27940-9_26",
volume = "7148",
pages = "396--411",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",

}

RIS

TY - CONF

T1 - A General Framework for Probabilistic Characterizing Formulae

A1 - Sack,Joshua

A1 - Zhang,Lijun

AU - Sack,Joshua

AU - Zhang,Lijun

PB - Springer

PY - 2012

Y1 - 2012

N2 - Recently, a general framework on characteristic formulae was proposed by Aceto et al. It offers a simple theory that allows one to easily obtain characteristic formulae of many non-probabilistic behavioral relations. Our paper studies their techniques in a probabilistic setting. We provide a general method for determining characteristic formulae of behavioral relations for probabilistic automata using fixed-point probability logics. We consider such behavioral relations as simulations and bisimulations, probabilistic bisimulations, probabilistic weak simulations, and probabilistic forward simulations. This paper shows how their constructions and proofs can follow from a single common technique.

AB - Recently, a general framework on characteristic formulae was proposed by Aceto et al. It offers a simple theory that allows one to easily obtain characteristic formulae of many non-probabilistic behavioral relations. Our paper studies their techniques in a probabilistic setting. We provide a general method for determining characteristic formulae of behavioral relations for probabilistic automata using fixed-point probability logics. We consider such behavioral relations as simulations and bisimulations, probabilistic bisimulations, probabilistic weak simulations, and probabilistic forward simulations. This paper shows how their constructions and proofs can follow from a single common technique.

UR - http://lara.epfl.ch/vmcai2012/

U2 - 10.1007/978-3-642-27940-9_26

DO - 10.1007/978-3-642-27940-9_26

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

VL - 7148

SP - 396

EP - 411

ER -