Computer
A logic for reasoning about probabilities
Information and Computation - Selections from 1988 IEEE symposium on logic in computer science
Logic and artificial intelligence
Artificial Intelligence
Bilattices and the semantics of logic programming
Journal of Logic Programming
Uncertainty, belief, and probability
Computational Intelligence
Two views of belief: belief as generalized probability and belief as evidence
Artificial Intelligence
A logic for reasoning with inconsistency
Journal of Automated Reasoning
Artificial Intelligence
Kleene's three valued logics and their children
Fundamenta Informaticae
A nonstandard approach to the logical omniscience problem
Artificial Intelligence
A semantics for reasoning consistently in the presence of inconsistency
Artificial Intelligence
Artificial Intelligence
Bilattices and Reasoning in ArtificialIntelligence: Concepts and Foundations
Artificial Intelligence Review
Current Approaches to Handling Imperfect Information in Data and Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
Using Dempster-Shafer theory in knowledge representation
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Reasoning about Uncertainty
ML-KNN: A lazy learning approach to multi-label learning
Pattern Recognition
An introduction to bipolar representations of information and preference
International Journal of Intelligent Systems
Bipolarity in bilattice logics
International Journal of Intelligent Systems - Bipolar Representations of Information and Preference Part 2: Reasoning and Learning
International Journal of Intelligent Systems - Decision Sciences: Foundations and Applications
The canonical decomposition of a weighted belief
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Believe it or not: adding belief annotations to databases
Proceedings of the VLDB Endowment
Decision making in the TBM: the necessity of the pignistic transformation
International Journal of Approximate Reasoning
The lattice of embedded subsets
Discrete Applied Mathematics
Representing uncertainty on set-valued variables using belief functions
Artificial Intelligence
A hybrid framework for representing uncertain knowledge
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Ensemble clustering in the belief functions framework
International Journal of Approximate Reasoning
Possibility and necessity functions over non-classical logic
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Transferable belief model for decision making in the valuation-based systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
What is an ideal logic for reasoning with inconsistency?
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
On truth-gaps, bipolar belief and the assertability of vague propositions
Artificial Intelligence
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The Dempster-Shafer theory of belief functions is an important approach to deal with uncertainty in AI. In the theory, belief functions are defined on Boolean algebras of events. In many applications of belief functions in real world problems, however, the objects that we manipulate is no more a Boolean algebra but a distributive lattice. In this paper, we employ Birkhoff@?s representation theorem for finite distributive lattices to extend the Dempster-Shafer theory to the setting of distributive lattices, which has a mathematical theory as attractive as in that of Boolean algebras. Moreover, we use this more general theory to provide a framework for reasoning about belief functions in a deductive approach on non-classical formalisms which assume a setting of distributive lattices. As an illustration of this approach, we investigate the theory of belief functions for a simple epistemic logic the first-degree-entailment fragment of relevance logic R by providing an axiomatization for reasoning about belief functions for this logic and by showing that the complexity of the satisfiability problem of a belief formula with respect to the class of the corresponding Dempster-Shafer structures is NP-complete.