Operations Research
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic inference and influence diagrams
Operations Research
Uncertainty Management in Expert Systems
IEEE Expert: Intelligent Systems and Their Applications
On Knowledge Representation in Belief Networks
IPMU '90 Proceedings of the 3rd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems: Uncertainty in Knowledge Bases
MUNIN: a causal probabilistic network for interpretation of electromyographic findings
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Paper: Multiply sectioned Bayesian networks for neuromuscular diagnosis
Artificial Intelligence in Medicine
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At last year's Uncertainty in AI Conference, we reported the results of a sensitivity analysis study of Pathfinder. Our findings were quite unexpected--slight variations to Pathfinder's parameters appeared to lead to substantial degradations in system performance. A careful look at our first analysis, together with the valuable feedback provided by the participants of last year's conference, led us to conduct a follow-up study. Our follow-up differs from our initial study in two ways: (i) the probabilities 0.0 and 1.0 remained unchanged, and (ii) the variations to the probabilities that are close to both ends (0.0 or 1.0) were less than the ones close to the middle (0.5). The results of the follow-up study look more reasonable--slight variations to Pathfinder's parameters now have little effect on its performance. Taken together, these two sets of results suggest a viable extension of a common decision analytic sensitivity analysis to the larger, more complex settings generally encountered in artificial intelligence.