Fundamental concepts of qualitative probabilistic networks
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
Efficient reasoning in qualitative probabilistic networks
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Incremental tradeoff resolution in qualitative probabilistic networks
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Refining reasoning in qualitative probabilistic networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Context-specific sign-propagation in qualitative probabilistic networks
Artificial Intelligence
Qualitative probability and order of magnitude reasoning
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
A review of explanation methods for Bayesian networks
The Knowledge Engineering Review
Complexity results for enhanced qualitative probabilistic networks
International Journal of Approximate Reasoning
Inference in qualitative probabilistic networks revisited
International Journal of Approximate Reasoning
Context-specific sign-propagation in qualitative probabilistic networks
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Introducing situational signs in qualitative probabilistic networks
International Journal of Approximate Reasoning
Qualitative probabilistic networks with reduced ambiguities
Applied Intelligence
Pivotal pruning of trade-offs in QPNs
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Upgrading ambiguous signs in QPNs
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
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Qualitative probabilistic networks have been introduced as qualitative abstractions of Bayesian belief networks. One of the major drawbacks of these qualitative networks is their coarse level of detail, which may lead to unresolved trade-offs during inference. We present an enhanced formalism for qualitative networks with a finer level of detail. An enhanced qualitative probabilistic network differs from a regular qualitative network in that it distinguishes between strong and weak influences. Enhanced qualitative probabilistic networks are purely qualitative in nature, as regular qualitative networks are, yet allow for efficiently resolving trade-offs during inference.