Artificial Intelligence
Artificial Intelligence - Special issue on knowledge representation
Elements of information theory
Elements of information theory
A theory of diagnosis from first principles
Readings in model-based diagnosis
Remote Agent: to boldly go where no AI system has gone before
Artificial Intelligence - Special issue: artificial intelligence 40 years later
Debugging sequential circuits using Boolean satisfiability
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
An Evaluation of Similarity Coefficients for Software Fault Localization
PRDC '06 Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing
Collaborative in-network processing for target tracking
EURASIP Journal on Applied Signal Processing
Temporal planning with mutual exclusion reasoning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Formal verification of diagnosability via symbolic model checking
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Representing diagnostic knowledge for probabilistic Horn abduction
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Dynamic multiple fault diagnosis: mathematical formulations and solution techniques
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Integration and test sequencing for complex systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Dynamic multiple-fault diagnosis with imperfect tests
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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In model-based production, a planner uses a system description to create plans that achieve production goals. The same description can be used by model-based diagnosis to infer the condition of components from sensor data. When production is realized by a sequence of plans, prior work has demonstrated that diagnosis can be used to adapt the plans to compensate for component degradation. However, the sources of diagnostic information are severely limited. Diagnosis must either make inferences from observations during production over which it has no control (passive diagnosis), or production must be halted to introduce diagnostic-specific plans (explicit diagnosis). We observe that the declarative nature of the model-based approach allows the planner to achieve production goals in multiple ways. This flexibility is exploited by a novel paradigm, i.e., pervasive (active) diagnosis, which constructs informative production plans that simultaneously achieve production goals while uncovering additional diagnostic information about the condition of components. We present an efficient heuristic search for these informative production plans and show through experiments on a model of an industrial digital printing press that the theoretical increase in long-run productivity can be realized on practical real-time systems. We obtain higher long-run productivity than a decoupled combination of planning and diagnosis.