Artificial Intelligence
A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Tree clustering for constraint networks (research note)
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Focusing on probable diagnosis
Readings in model-based diagnosis
Characterizing diagnoses and systems
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Building problem solvers
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Structure-driven algorithms for truth maintenance
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A logical notion of conditional independence: properties and applications
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IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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The effect of observations on the complexity of model-based diagnosis
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
An evaluation of structural parameters for probabilistic reasoning: results on benchmark circuits
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Decomposable negation normal form
Journal of the ACM (JACM)
Probabilistic Argumentation Systems and Abduction
Annals of Mathematics and Artificial Intelligence
Improving the Efficiency of Reasoning Through Structure-Based Reformulation
SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
Interpolation Theorems for Nonmonotonic Reasoning Systems
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
First order LUB approximations: characterization and algorithms
Artificial Intelligence - Special volume on reformulation
Study of the diagnosability of automated production systems based on functional graphs
Mathematics and Computers in Simulation - Special issue: Computational engineering in systems applications (CESA 2003)
A constraint solver for model-based engineering
AI Communications
On the role of modeling causal independence for system model compilation with OBDDs
AI Communications - Model-Based Systems
Distributed Consistency-Based Diagnosis
LPAR '08 Proceedings of the 15th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning
An Empirical Analysis of the Complexity of Model-Based Diagnosis
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
The Probabilistic Interpretation of Model-Based Diagnosis
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A two-step hierarchical algorithm for model-based diagnosis
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
On compiling system models for faster and more scalable diagnosis
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
A spectrum of symbolic on-line diagnosis approaches
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Generating application-specific benchmark models for complex systems
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Incremental algorithms for approximate compilation
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Propositional independence: formula-variable independence and forgetting
Journal of Artificial Intelligence Research
Utilizing device behavior in structure-based diagnosis
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Automated benchmark model generators for model-based diagnostic inference
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Automatic abstraction in component-based diagnosis driven by system observability
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A novel framework for integrating discrete event system control and diagnosis
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Hierarchical representation of complex systems for supporting human decision making
Advanced Engineering Informatics
Model compilation for real-time planning and diagnosis with feedback
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
First order LUB approximations: characterization and algorithms
Artificial Intelligence - Special volume on reformulation
Study of the diagnosability of automated production systems based on functional graphs
Mathematics and Computers in Simulation
An algorithm for diagnosing system with structured description
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartII
A benchmark diagnostic model generation system
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on model-based diagnostics
Approximate model-based diagnosis using greedy stochastic search
Journal of Artificial Intelligence Research
Efficient query processing with compiled knowledge bases
TABLEAUX'05 Proceedings of the 14th international conference on Automated Reasoning with Analytic Tableaux and Related Methods
Model-Based monitoring and diagnosis chip for embedded systems
AIMSA'06 Proceedings of the 12th international conference on Artificial Intelligence: methodology, Systems, and Applications
Model-Based diagnosis through OBDD compilation: a complexity analysis
Reasoning, Action and Interaction in AI Theories and Systems
Approximate model-based diagnosis using preference-based compilation
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
An evidential network approach to support uncertain multiviewpoint abductive reasoning
Information Sciences: an International Journal
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This paper presents a comprehensive approach for model-based diagnosis which includes proposals for characterizing and computing preferred diagnoses, assuming that the system description is augmented with a system structure (a directed graph explicating the interconnections between system components). Specifically, we first introduce the notion of a consequence, which is a syntactically unconstrained propositional sentence that characterizes all consistency-based diagnoses and show that standard characterizations of diagnoses, such as minimal conflicts, correspond to syntactic variations on a consequence. Second, we propose a new syntactic variation on the consequence known as negation normal form (NNF) and discuss its merits compared to standard variations. Third, we introduce a basic algorithm for computing consequences in NNF given a structured system description. We show that if the system structure does not contain cycles, then there is always a linear-size consequence in NNF which can be computed in linear time. For arbitrary system structures, we show a precise connection between the complexity of computing consequences and the topology of the underlying system structure. Finally, we present an algorithm that enumerates the preferred diagnoses characterized by a consequence. The algorithm is shown to take linear time in the size of the consequence if the preference criterion satisfies some general conditions.