Artificial Intelligence
All I know: a study in autoepistemic logic
Artificial Intelligence
Updating logical databases
Propositional knowledge base revision and minimal change
Artificial Intelligence
On the semantics of updates in databases
PODS '83 Proceedings of the 2nd ACM SIGACT-SIGMOD symposium on Principles of database systems
Conditional Logics for Default Reasoning and Belief Revision
Conditional Logics for Default Reasoning and Belief Revision
On the semantics of counterfactuals
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Inaccessible worlds and irrelevance preliminary report
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
The probability of a possibility: adding uncertainty to default rules
UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence
Modal logics for qualitative possibility and beliefs
UAI'92 Proceedings of the Eighth international conference on Uncertainty in artificial intelligence
| Hi-index | 0.00 |
We present a logic for belief revision in which revision of a theory by a sentence is represented using a conditional connective. The conditional is not primitive, but rather defined using two unary modal operators. Our approach captures and extends the classic AGM model without relying on the Limit Assumption. Reasoning about counterfactual or hypothetical situations is also crucial for AI. Existing logics for such subjunctive queries are lacking in several respects, however, primarily in failing to make explicit the epistemic nature of such queries. We present a logical model for subjunctives based on our logic of revision that appeals explicitly to the Ramsey test. We discuss a framework for answering subjunctive queries, and show how integrity constraints on the revision process can be expressed.