The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Second generation expert systems
Future Generation Computer Systems
Learning in second generation expert systems
Knowledge based problem solving
A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Defining operationality for explanation-based learning
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Model-based reasoning: troubleshooting
Exploring artificial intelligence
Integrating classification-based compiled level reasoning with function-based deep level reasoning
Applied Artificial Intelligence
KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
Abductive inference models for diagnostic problem-solving
Abductive inference models for diagnostic problem-solving
Using crude probability estimates to guide diagnosis
Artificial Intelligence
Hierarchical model-based diagnosis
International Journal of Man-Machine Studies
The computational complexity of abduction
Artificial Intelligence - Special issue on knowledge representation
AI Communications
A spectrum of logical definitions of model-based diagnosis
Computational Intelligence
The roles of associational and causal reasoning in problem solving
Artificial Intelligence
Formalizing the repair process
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Characterizing diagnoses and systems
Artificial Intelligence
Combining heuristic reasoning with causal reasoning in diagnostic problem solving
Second generation expert systems
Case-based reasoning
Diagnostic Problem Solving: Combining Heuristic, Approximate and Casual Reasoning
Diagnostic Problem Solving: Combining Heuristic, Approximate and Casual Reasoning
Knowledge Compilation: A Symposium
IEEE Expert: Intelligent Systems and Their Applications
Explanation-Based Generalization: A Unifying View
Machine Learning
Explanation-Based Learning: An Alternative View
Machine Learning
What is the most likely diagnosis?
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Problem Solver Control Over the ATMS
GWAI '89 Proceedings of the 13th German Workshop on Artificial Intelligence
CAUSAL REPRESENTATION OF PATIENT ILLNESS FOR ELECTROLYTE AND ACID-BASE DIAGNOSIS
CAUSAL REPRESENTATION OF PATIENT ILLNESS FOR ELECTROLYTE AND ACID-BASE DIAGNOSIS
ACM Computing Surveys (CSUR)
Monotonic reductions, representative equivalence, and compilation of intractable problems
Journal of the ACM (JACM)
Local Reasoning and Knowledge Compilation for Efficient Temporal Abduction
IEEE Transactions on Knowledge and Data Engineering
Later: Managing Temporal Information Efficiently
IEEE Expert: Intelligent Systems and Their Applications
Abduction in Logic Programming
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part I
Incremental development of diagnostic set-covering models with therapy effects
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Compilability of propositional abduction
ACM Transactions on Computational Logic (TOCL)
Fuzzy theory approach for temporal model-based diagnosis: An application to medical domains
Artificial Intelligence in Medicine
Abductive Logic Programming in the Clinical Management of HIV/AIDS
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Approximate compilation for embedded model-based reasoning
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Model-based diagnosis in the real world: lessons learned and challenges remaining
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
A-system: problem solving through abduction
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
A fuzzy temporal diagnosis algorithm and a hypothesis discrimination proposal
IWINAC'05 Proceedings of the First international conference on Mechanisms, Symbols, and Models Underlying Cognition: interplay between natural and artificial computation - Volume Part I
Approximate model-based diagnosis using preference-based compilation
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Multiple representations and multi-modal reasoning in medical diagnostic systems
Artificial Intelligence in Medicine
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Several artificial intelligence architectures and systems based on "deep" models of a domain have been proposed, in particular for the diagnostic task. These systems have several advantages over traditional knowledge based systems, but they have a main limitation in their computational complexity. One of the ways to face this problem is to rely on a knowledge compilation phase, which produces knowledge that can be used more effectively with respect to the original one.In this paper we show how a specific knowledge compilation approach can focus reasoning in abductive diagnosis, and, in particular, can improve the performances of AID, an abductive diagnosis system. The approach aims at focusing the overall diagnostic cycle in two interdependent ways: avoiding the generation of candidate solutions to be discarded a posteriori and integrating the generation of candidate solutions with discrimination among different candidates. Knowledge compilation is used off-line to produce operational (i.e., easily evaluated) conditions that embed the abductive reasoning strategy and are used in addition to the original model, with the goal of ruling out parts of the search space or focusing on parts of it. The conditions are useful to solve most cases using less time for computing the same solutions, yet preserving all the power of the model-based system for dealing with multiple faults and explaining the solutions. Experimental results showing the advantages of the approach are presented.