Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
On the generation of alternative explanations with implications for belief revision
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
A linear constraint satisfaction approach to cost-based abduction
Artificial Intelligence
Simulation Approaches to General Probabilistic Inference on Belief Networks
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
A new algorithm for finding MAP assignments to belief networks
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Dynamic construction of belief networks
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
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
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
An efficient approach for finding the MPE in belief networks
UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence
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We present a dynamic algorithm for MAP calculations. The algorithm is based upon Santos's technique (Santos 1991b) of transforming minimal-cost-proof problems into linear-programming problems. The algorithm is dynamic in the sense that it is able to use the results from an earlier, near by, problem to lessen its search time. Results are presented which clearly suggest that this is a powerful technique for dynamic abduction problems.