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Model checking with probabilistic tabled logic programming

Published online by Cambridge University Press:  05 September 2012

ANDREY GORLIN ,
C. R. RAMAKRISHNAN  and
SCOTT A. SMOLKA
ANDREY GORLIN
Affiliation:
Department of Computer Science, Stony Brook University, Stony Brook, NY 11794-4400, USA (e-mail: agorlin@cs.stonybrook.edu, cram@cs.stonybrook.edu, sas@cs.stonybrook.edu)
C. R. RAMAKRISHNAN
Affiliation:
Department of Computer Science, Stony Brook University, Stony Brook, NY 11794-4400, USA (e-mail: agorlin@cs.stonybrook.edu, cram@cs.stonybrook.edu, sas@cs.stonybrook.edu)
SCOTT A. SMOLKA
Affiliation:
Department of Computer Science, Stony Brook University, Stony Brook, NY 11794-4400, USA (e-mail: agorlin@cs.stonybrook.edu, cram@cs.stonybrook.edu, sas@cs.stonybrook.edu)
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Abstract

We present a formulation of the problem of probabilistic model checking as one of query evaluation over probabilistic logic programs. To the best of our knowledge, our formulation is the first of its kind, and it covers a rich class of probabilistic models and probabilistic temporal logics. The inference algorithms of existing probabilistic logic-programming systems are well defined only for queries with a finite number of explanations. This restriction prohibits the encoding of probabilistic model checkers, where explanations correspond to executions of the system being model checked. To overcome this restriction, we propose a more general inference algorithm that uses finite generative structures (similar to automata) to represent families of explanations. The inference algorithm computes the probability of a possibly infinite set of explanations directly from the finite generative structure. We have implemented our inference algorithm in XSB Prolog, and use this implementation to encode probabilistic model checkers for a variety of temporal logics, including PCTL and GPL (which subsumes PCTL*). Our experiment results show that, despite the highly declarative nature of their encodings, the model checkers constructed in this manner are competitive with their native implementations.

Information

Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 12 , Issue 4-5: 28th International Conference on Logic Programming , July 2012 , pp. 681 - 700
Copyright
Copyright © Cambridge University Press 2012

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