Propositional knowledge base revision and minimal change
Artificial Intelligence
On the logic of iterated belief revision
Artificial Intelligence
Dynamic belief revision operators
Artificial Intelligence
Reasoning about Uncertainty
On the revision of probabilistic beliefs using uncertain evidence
Artificial Intelligence
Iterated belief revision, revised
Artificial Intelligence
Plausibility measures: a general approach for representing uncertainty
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Revision of partially ordered information: axiomatization, semantics and iteration
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A distance measure for bounding probabilistic belief change
International Journal of Approximate Reasoning
Plausibility measures: a user's guide
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Belief revision of product-based causal possibilistic networks
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Revision over partial pre-orders: a postulational study
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
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In this paper, we present a general revision model on epistemic states based on plausibility measures proposed by Friedman and Halpern. We propose our revision strategy and give some desirable properties, e.g., the reversible and commutative properties. Moreover, we develop a notion called plausibility kinematics and show that our revision strategy follows plausibility kinematics. Furthermore, we prove that the revision following plausibility kinematics satisfies the principle of minimal change based on some distance measures. Finally, we discuss a revision operator defined for plausibility functions and its relationship with iterated belief revision proposed by Darwiche and Pearl. We show that the revision operator satisfies all the DP postulates when it is Max-Additive.