A logical framework for default reasoning
Artificial Intelligence
Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Propositional knowledge base revision and minimal change
Artificial Intelligence
What does a conditional knowledge base entail?
Artificial Intelligence
Abduction versus closure in causal theories
Artificial Intelligence
On the semantics of theory change: arbitration between old and new information
PODS '93 Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
View updates in stratified disjunctive databases
Journal of Automated Reasoning
Nonmonotonic inference based on expectations
Artificial Intelligence
From ordering-based nonmonotonic reasoning to conditional logics
Artificial Intelligence
The complexity of logic-based abduction
Journal of the ACM (JACM)
Updates and subjunctive queries
Information and Computation
Artificial Intelligence
Abductive consequence relations
Artificial Intelligence
A semantic charcterization of disjunctive relations
FAIR '91 Proceedings of the International Workshop on Fundamentals of Artificial Intelligence Research
Database Updates through Abduction
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
Relations between the logic of theory change and nonmonotonic logic
Proceedings of the Workshop on The Logic of Theory Change
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This paper describes a change theory based on abductive reasoning. We take the AGM postulates for revisions, expansions and contractions, and Katsuno and Mendelzon postulates for updates and incorporate abduction into them. A key feature of the theory is that presents a unified view of standard change operators and abductive change operators rather than a new and independent change theory for abductive changes. Abductive operators reduce to standard change operators in the limiting cases.