The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Abductive inference models for diagnostic problem-solving
Abductive inference models for diagnostic problem-solving
Optimization
A probabilistic approach to language understanding
A probabilistic approach to language understanding
Cost-Based Abduction and Linear Constraint Satisfaction
Cost-Based Abduction and Linear Constraint Satisfaction
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
Prediction is deduction but explanation is abduction
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Probabilistic semantics for cost based abduction
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Abductive and default reasoning: a computational core
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Context Hypothesization Using Probabilistic Knowledge
Fundamenta Informaticae
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In general, the best explanation for a given observation makes no promises on how good it is with respect to other alternative explanations. A major deficiency of message-passing schemes for belief revision in Bayesian networks is their inability to generate alternatives beyond the second best. In this paper, we present a general approach based on linear constraint systems that naturally generates alternative explanations in an orderly and highly efficient manner. This approach is then applied to cost-based abduction problems as well as belief revision in Bayesian networks.