Model equivalence of PRISM programs

James Cussens

doi:10.4230/DagSemProc.07161.7

Model equivalence of PRISM programs

James Cussens

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

The problem of deciding the probability model equivalence of two PRISM programs is addressed. In the finite case this problem can be solved (albeit slowly) using techniques from emph{algebraic statistics}, specifically the computation of elimination ideals and Gr"{o}bner bases. A very brief introduction to algebraic statistics is given. Consideration is given to cases where shortcuts to proving/disproving model equivalence are available.

Original language	English
Title of host publication	Probabilistic, Logical and Relational Learning - A Further Synthesis
Subtitle of host publication	Dagstuhl Seminar Proceedings
Pages	1-21
Volume	7161
DOIs	https://doi.org/10.4230/DagSemProc.07161.7
Publication status	Published - 6 Mar 2008

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title = "Model equivalence of PRISM programs",

abstract = "The problem of deciding the probability model equivalence of two PRISM programs is addressed. In the finite case this problem can be solved (albeit slowly) using techniques from emph\{algebraic statistics\}, specifically the computation of elimination ideals and Gr{"}\{o\}bner bases. A very brief introduction to algebraic statistics is given. Consideration is given to cases where shortcuts to proving/disproving model equivalence are available. ",

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AB - The problem of deciding the probability model equivalence of two PRISM programs is addressed. In the finite case this problem can be solved (albeit slowly) using techniques from emph{algebraic statistics}, specifically the computation of elimination ideals and Gr"{o}bner bases. A very brief introduction to algebraic statistics is given. Consideration is given to cases where shortcuts to proving/disproving model equivalence are available.

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DO - 10.4230/DagSemProc.07161.7

M3 - Conference Contribution (Conference Proceeding)

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BT - Probabilistic, Logical and Relational Learning - A Further Synthesis

ER -

Model equivalence of PRISM programs

Abstract

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