Uncertainty in artificial intelligence: Is probability epistemologically and heuristically accurate?
Expert judgment and expert systems
Embracing causality in fault reasoning
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Fundamental concepts of qualitative probabilistic networks
Artificial Intelligence
Formulation of tradeoffs in planning under uncertainty
Formulation of tradeoffs in planning under uncertainty
Search-based methods to bound diagnostic probabilities in very large belief nets
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
Evidence Absorption and Propagation through Evidence Reversals
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Qualtitative propagation and scenario-based scheme for exploiting probabilistic reasoning
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Building a Bayesian network model of heart disease
ACM-SE 38 Proceedings of the 38th annual on Southeast regional conference
Towards qualitative approaches to Bayesian evidential reasoning
Proceedings of the 11th international conference on Artificial intelligence and law
A spatio-temporal Bayesian network classifier for understanding visual field deterioration
Artificial Intelligence in Medicine
Efficient reasoning in qualitative probabilistic networks
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
On extracting arguments from Bayesian network representations of evidential reasoning
Proceedings of the 13th International Conference on Artificial Intelligence and Law
Elicitation of probabilities for belief networks: combining qualitative and quantitative information
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
An experimental comparison of numerical and qualitative probabilistic reasoning
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Most relevant explanation in Bayesian networks
Journal of Artificial Intelligence Research
Qualitative chain graphs and their application
International Journal of Approximate Reasoning
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'Explaining away' is a common pattern of reasoning in which the confirmation of one cause of an observed or believed event reduces the need to invoke alternative causes. The opposite of explaining away also an occur, where the confirmation of one cause increases belief in another. A general qualitative probabilistic analysis of intercausal reasoning is provided and the property of the interaction among the causes (product synergy) that determines which form of reasoning is appropriate is identified. Product synergy extends the qualitative probabilistic network (QPN) formalism to support qualitative intercausal inference about the directions of change in probabilistic belief. The intercausal relation also justifies Occam's razor, facilitating pruning in the search for likely diagnoses.