Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Reasoning with qualitative probabilities can be tractable
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Relevance and Revision - About Generalizing Syntax-based Belief Revision
JELIA '92 Proceedings of the European Workshop on Logics in AI
A general non-probabilistic theory of inductive reasoning
UAI '88 Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
Qualitative Magnitude Reasoning
Proceedings of the 1st International Workshop on Nonmonotonic and Inductive Logic
Relations between the logic of theory change and nonmonotonic logic
Proceedings of the Workshop on The Logic of Theory Change
Revisions of knowledge systems using epistemic entrenchment
TARK '88 Proceedings of the 2nd conference on Theoretical aspects of reasoning about knowledge
Possibilistic logic, preferential models, non-monotonicity and related issues
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
A symbolic generalization of probability theory
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Ranking functions and rankings on languages
Artificial Intelligence
A framework for managing uncertain inputs: An axiomization of rewarding
International Journal of Approximate Reasoning
Projective default epistemology
WCII'02 Proceedings of the 2002 international conference on Conditionals, Information, and Inference
On the plausibility of abstract arguments
ECSQARU'13 Proceedings of the 12th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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Probability measures by themselves are known to be inappropriate for modeling the dynamics of plain belief and their excessively strong measurability constraints make them unsuitable for some representational tasks, e.g. in the context of first-order knowledge. In this paper, we are therefore going to look for possible alternatives and extensions. We begin by delimiting the general area of interest, proposing a minimal list of assumptions to be satisfied by any reasonable quasi-probabilistic valuation concept. Within this framework, we investigate two particularly interesting kinds of quasi-measures which are not or much less affected by the traditional problems. • Ranking measures, which generalize Spohntype and possibility measures. • Cumulative measures, which combine the probabilistic and the ranking philosophy, allowing thereby a fine-grained account of static and dynamic belief.