Expert systems and fuzzy systems
Expert systems and fuzzy systems
Properties of measures of information in evidence and possibility theories
Fuzzy Sets and Systems - Special Issue: Measures of Uncertainty
The principle of minimum specificity as a basis for evidential reasoning
Processing and Management of Uncertainty in Knowledge-Based Systems on Uncertainty in knowledge-based systems. International Conference on Information
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Combining opinions from several experts
Applied Artificial Intelligence
Reasoning with belief functions: an analysis of compatibility
International Journal of Approximate Reasoning
Consonant approximation of belief functions
International Journal of Approximate Reasoning
A logic-based analysis of Dempster-Shafer theory
International Journal of Approximate Reasoning
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
From Petri Nets to Linear Logic
Category Theory and Computer Science
An inference technique for integrating knowledge from disparate sources
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Uncertainty, belief, and probability
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Combining bodies of dependent information
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Characterizing belief with minimum commitment
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Two views of belief: belief as generalized probability and belief as evidence
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
The belief calculus and uncertain reasoning
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
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The categorial approach to evidential reasoning can be seen as a combination of the probability kinematics approach of Richard Jeffrey (1965) and the maximum (cross-) entropy inference approach of E. T. Jaynes (1957). As a consequence of that viewpoint, it is well known that category theory provides natural definitions for logical connectives. In particular, disjunction and conjunction are modelled by general categorial constructions known as products and coproducts. In this paper, I focus mainly on Dempster-Shafer theory of belief functions for which I introduce a category I call Dempster's category. I prove the existence of and give explicit formulas for conjunction and disjunction in the subcategory of separable belief functions. In Dempster's category, the new defined conjunction can be seen as the most cautious conjunction of beliefs, and thus no assumption about distinctness (of the sources) of beliefs is needed as opposed to Dempster's rule of combination, which calls for distinctness (of the sources) of beliefs.