The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
A theory of diagnosis from first principles
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Dynamic construction of belief networks
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
On Irrelevance and Partial Assignments to Belief Networks
On Irrelevance and Partial Assignments to Belief Networks
A New Admissible Heuristic for Minimal-Cost Proofs
A New Admissible Heuristic for Minimal-Cost Proofs
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
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Neural Networks - 2005 Special issue: IJCNN 2005
Cost-sharing in Bayesian knowledge bases
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Belief updating by enumerating high-probabilityindependence-based assignments
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
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Finding best explanations is often formalized in AI in terms of minimal-cost proofs. Finding such proofs is naturally characterized as a best-first search of the proof-tree (actually a proof dag). Unfortunately the only known search heuristic for this task is quite poor. In this paper we present a new heuristic, a proof that it is admissible (for certain successor functions), and some experimental results suggesting that it is a significant improvement over the currently used heuristic.