Compiling model-based diagnosis to Boolean satisfaction

Amit Metodi; Roni Stern; Meir Kalech; Michael Codish

Compiling model-based diagnosis to Boolean satisfaction

Amit Metodi, Roni Stern, Meir Kalech, Michael Codish

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

25 Scopus citations

Abstract

This paper introduces an encoding of Model Based Diagnosis (MBD) to Boolean Satisfaction (SAT) focusing on minimal cardinality diagnosis. The encoding is based on a combination of sophisticated MBD preprocessing algorithms and SAT compilation techniques which together provide concise CNF formula. Experimental evidence indicates that our approach is superior to all published algorithms for minimal cardinality MBD. In particular, we can determine, for the first time, minimal cardinality diagnoses for the entire standard ISCAS-85 benchmark. Our results open the way to improve the state-of-the-art on a range of similar MBD problems.

Original language	English
Title of host publication	AAAI-12 / IAAI-12 - Proceedings of the 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference
Pages	793-799
Number of pages	7
State	Published - 7 Nov 2012
Event	26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12 - Toronto, ON, Canada Duration: 22 Jul 2012 → 26 Jul 2012

Publication series

Name	Proceedings of the National Conference on Artificial Intelligence
Volume	1

Conference

Conference	26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12
Country/Territory	Canada
City	Toronto, ON
Period	22/07/12 → 26/07/12

ASJC Scopus subject areas

Software
Artificial Intelligence

Cite this

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title = "Compiling model-based diagnosis to Boolean satisfaction",

abstract = "This paper introduces an encoding of Model Based Diagnosis (MBD) to Boolean Satisfaction (SAT) focusing on minimal cardinality diagnosis. The encoding is based on a combination of sophisticated MBD preprocessing algorithms and SAT compilation techniques which together provide concise CNF formula. Experimental evidence indicates that our approach is superior to all published algorithms for minimal cardinality MBD. In particular, we can determine, for the first time, minimal cardinality diagnoses for the entire standard ISCAS-85 benchmark. Our results open the way to improve the state-of-the-art on a range of similar MBD problems.",

author = "Amit Metodi and Roni Stern and Meir Kalech and Michael Codish",

year = "2012",

month = nov,

day = "7",

language = "English",

isbn = "9781577355687",

series = "Proceedings of the National Conference on Artificial Intelligence",

pages = "793--799",

booktitle = "AAAI-12 / IAAI-12 - Proceedings of the 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference",

note = "26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12 ; Conference date: 22-07-2012 Through 26-07-2012",

}

Metodi, A, Stern, R , Kalech, M & Codish, M 2012, Compiling model-based diagnosis to Boolean satisfaction. in AAAI-12 / IAAI-12 - Proceedings of the 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference. Proceedings of the National Conference on Artificial Intelligence, vol. 1, pp. 793-799, 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12, Toronto, ON, Canada, 22/07/12.

Compiling model-based diagnosis to Boolean satisfaction. / Metodi, Amit; Stern, Roni ; Kalech, Meir et al.
AAAI-12 / IAAI-12 - Proceedings of the 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference. 2012. p. 793-799 (Proceedings of the National Conference on Artificial Intelligence; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - This paper introduces an encoding of Model Based Diagnosis (MBD) to Boolean Satisfaction (SAT) focusing on minimal cardinality diagnosis. The encoding is based on a combination of sophisticated MBD preprocessing algorithms and SAT compilation techniques which together provide concise CNF formula. Experimental evidence indicates that our approach is superior to all published algorithms for minimal cardinality MBD. In particular, we can determine, for the first time, minimal cardinality diagnoses for the entire standard ISCAS-85 benchmark. Our results open the way to improve the state-of-the-art on a range of similar MBD problems.

AB - This paper introduces an encoding of Model Based Diagnosis (MBD) to Boolean Satisfaction (SAT) focusing on minimal cardinality diagnosis. The encoding is based on a combination of sophisticated MBD preprocessing algorithms and SAT compilation techniques which together provide concise CNF formula. Experimental evidence indicates that our approach is superior to all published algorithms for minimal cardinality MBD. In particular, we can determine, for the first time, minimal cardinality diagnoses for the entire standard ISCAS-85 benchmark. Our results open the way to improve the state-of-the-art on a range of similar MBD problems.

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M3 - Conference contribution

AN - SCOPUS:84868273803

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Y2 - 22 July 2012 through 26 July 2012

ER -

Compiling model-based diagnosis to Boolean satisfaction

Abstract

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Conference

ASJC Scopus subject areas

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