How to clear a block: A theory of plans
Journal of Automated Reasoning
An approach to default reasoning based on a first-order conditional logic: revised report
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Miracles in formal theories of action
Artificial Intelligence
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
What does a conditional knowledge base entail?
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Conditional logics for default reasoning and belief revision
Conditional logics for default reasoning and belief revision
Is it Impossible to Keep up to Date?
Proceedings of the 1st International Workshop on Nonmonotonic and Inductive Logic
Discourse representation theory and belief dynamics
Proceedings of the Workshop on The Logic of Theory Change
System Z: A Natural Ordering of Defaults with Tractable Applications to Nonmonotonic Reasoning
Proceedings of the 3rd Conference on Theoretical Aspects of Reasoning about Knowledge
| Hi-index | 0.00 |
Several authors (Keller and Winslett 1985, Winslett 1988, Katsuno and Mendelzon 1989, Morreau and Rott 1991) have recently argued for a distinction in the way beliefs are updated with new information. They distinguish between information that tells the agent that the world has changed over time and information that fills in or corrects the agent's picture of the world at a particular time. We provide an explicit representation of this distinction by means of a modal logic that combines epistemic and dynamic features. Furthermore, we develop a completely declarative semantics for belief revision. This semantics enables us to deduce the result of revising a given body of beliefs in the light of new information, given simply the semantic content of the prior beliefs and of the new data. No purely procedural assumptions about the agent's epistemic policies or values (no information about priorities of defaults or degrees of entrenchment) are needed, beyond what is explicitly represented in the objects of the agent's beliefs. We accomplish this by distinguishing hard (incorrigible, unrevisable) belief and soft belief; further, the soft attitudes supervene on the hard level. We use a specific theory of nonmonotonic inference to generate soft attitudes from hard ones. This last point is especially important in attempting to deal with belief change, because when an agent acquires new beliefs there is the question: what beliefs about the world persist? We think that only a nonmonotonic logic can adequately deal with this question in a sufficiently rich framework for belief revision like the one we propose.