Structures of rule-based belief functions
IBM Journal of Research and Development
Certainty-Factor-Like Structures in Bayesian Networks
AI*IA '99 Proceedings of the 6th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
Use of Elvira's explanation facility for debugging probabilistic expert systems
Knowledge-Based Systems
Using qualitative hypotheses to identify inaccurate data
Journal of Artificial Intelligence Research
Exploiting causal independence in Bayesian network inference
Journal of Artificial Intelligence Research
A method of computing generalized Bayesian probability values for expert systems
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Prolog-ELF incorporating fuzzy logic
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
Preliminary performance analysis of the prospector consultant system for mineral exploration
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 1
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Parallel formulation op evidential-reasoning theories
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Flexible data fusion (& fission)
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Heuristic reasoning and relative incompleteness
International Journal of Approximate Reasoning
On the expressiveness of rule-based systems for reasoning with uncertainty
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
The logic of representing dependencies by directed graphs
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
On the expressiveness of rule-based systems for reasoning with uncertainty
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
The logic of representing dependencies by directed graphs
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
Approximate reasoning systems: a personal perspective
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
BIMBO: a system which learns its expertise
PKWBS-W'84 Proceedings of the 1984 IEEE conference on Principles of knowledge-based systems
Self-organizing ARTMAP rule discovery
Neural Networks
Learning the bias of a classifier in a GA-Based inductive learning environment
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Certainty factor theory: Its probabilistic interpretations and problems
Artificial Intelligence in Medicine
Application of rough set theory for clinical data analysis: A case study
Mathematical and Computer Modelling: An International Journal
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The general problem of drawing inferences from uncertain or incomplete evidence has invited a variety of technical approaches, some mathematically rigorous and some largely informal and intuitive. Most current inference systems in artificial intelligence have emphasized intuitive methods, because the absence of adequate statistical samples forces a reliance on the subjective judgment of human experts. We describe in this paper a subjective Bayesian inference method that realizes some of the advantages of both formal and informal approaches. Of particular interest are the modifications needed to deal with the inconsistencies usually found in collections of subjective statements.