Propositional knowledge base revision and minimal change
Artificial Intelligence
Qualitative probabilities: a normative framework for commonsense reasoning
Qualitative probabilities: a normative framework for commonsense reasoning
On the logic of iterated belief revision
Artificial Intelligence
Revisions of Knowledge Systems Using Epistemic Entrenchment
Proceedings of the 2nd Conference on Theoretical Aspects of Reasoning about Knowledge
Changing Conditional Belief Unconditionally
Proceedings of the Sixth Conference on Theoretical Aspects of Rationality and Knowledge
Proceedings of the Sixth Conference on Theoretical Aspects of Rationality and Knowledge
Proceedings of the Workshop on The Logic of Theory Change
Dynamic belief revision operators
Artificial Intelligence
On the logic of iterated belief revision
TARK '94 Proceedings of the 5th conference on Theoretical aspects of reasoning about knowledge
A negotiation-style framework for non-prioritised revision
TARK '01 Proceedings of the 8th conference on Theoretical aspects of rationality and knowledge
On the Use of an Extended Relational Model to Handle Changing Incomplete Information
IEEE Transactions on Software Engineering
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Expressing Belief Flow in Assertion Networks
Logic, Language, and Computation
Reasoning with Prioritized Data by Aggregation of Distance Functions
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
A General Model for Epistemic State Revision using Plausibility Measures
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Using Transfinite Ordinal Conditional Functions
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Mutual belief revision: semantics and computation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
A semantic approach for iterated revision in possibilistic logic
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
On the measure of conflicts: Shapley Inconsistency Values
Artificial Intelligence
Extending Removed Sets Revision to partially preordered belief bases
International Journal of Approximate Reasoning
AGM belief revision in dynamic games
Proceedings of the 13th Conference on Theoretical Aspects of Rationality and Knowledge
Iterated belief change due to actions and observations
Journal of Artificial Intelligence Research
A framework for managing uncertain inputs: An axiomization of rewarding
International Journal of Approximate Reasoning
NO Revision and NO Contraction
Minds and Machines
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Parallel belief revision: Revising by sets of formulas
Artificial Intelligence
Revising beliefs on the basis of evidence
International Journal of Approximate Reasoning
Revising by an inconsistent set of formulas
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Managing software requirements changes based on negotiation-style revision
Journal of Computer Science and Technology - Special issue on Community Analysis and Information Recommendation
Revision over partial pre-orders: a postulational study
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
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The AGM postulates for belief revision, augmented by the DP postulates for iterated belief revision, provide widely accepted criteria for the design of operators by which intelligent agents adapt their beliefs incrementally to new information. These postulates alone, however, are too permissive: They support operators by which all newly acquired information is canceled as soon as an agent learns a fact that contradicts some of its current beliefs. In this paper, we present a formal analysis of the deficiency of the standard postulates alone, and we show how to solve the problem by an additional postulate of independence. We give a representation theorem for this postulate and prove that it is compatible with AGM and DP.