An introduction to possibilistic and fuzzy logics
Readings in uncertain reasoning
A model for reasoning about persistence and causation
Computational Intelligence
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Probabilistic semantics for nonmonotonic reasoning: a survey
Proceedings of the first international conference on Principles of knowledge representation and reasoning
A symbolic generalization of probability theory
A symbolic generalization of probability theory
Fuzzy Measure Theory
A knowledge-based framework for belief change part I: foundations
TARK '94 Proceedings of the 5th conference on Theoretical aspects of reasoning about knowledge
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Generalized update: belief change in dynamic settings
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Plausibility measures and default reasoning
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Provably correct theories of action
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
Numerical representations of acceptance
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Plausibility measures: a user's guide
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Complexity, ontology, and the causal Markov assumption
ACM SIGART Bulletin
Belief revision with unreliable observations
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Plausibility measures and default reasoning
Journal of the ACM (JACM)
Modeling belief in dynamic systems part II: revision and update
Journal of Artificial Intelligence Research
Plausibility measures: a general approach for representing uncertainty
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Plausibility measures and default reasoning
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Plausibility measures: a user's guide
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
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The study of belief change has been an active area in philosophy and AI. In recent years, two special cases of belief change, belief revision and belief update, have been studied in detail. Roughly speaking, revision treats a surprising observation as a sign that previous beliefs were wrong, while update treats a surprising observation as an indication that the world has changed. In general, we would expect that an agent making an observation may both want to revise some earlier beliefs and assume that some change has occurred in the world. We define a novel approach to belief change that allows us to do this, by applying ideas from probability theory in a qualitative settings. The key idea is to use a qualitative Markov assumption, which says that state transitions are independent. We show that a recent approach to modeling qualitative uncertainty using plausibility measures allows us to make such a qualitative Markov assumption in a relatively straightforward way, and show how the Markov assumption can be used to provide an attractive belief-change model.