Introduction to artificial intelligence
Introduction to artificial intelligence
On the relation between default and autoepistemic logic
Artificial Intelligence
Abductive inference models for diagnostic problem-solving
Abductive inference models for diagnostic problem-solving
A catalog of complexity classes
Handbook of theoretical computer science (vol. A)
Hard problems for simple default logics
Artificial Intelligence - Special issue on knowledge representation
Abduction versus closure in causal theories
Artificial Intelligence
Reasoning with parsimonious and moderately grounded expansions
Fundamenta Informaticae - Special issue on modal logics in knowledge representation
Database Updates through Abduction
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
The Complexity of Logic-Based Abduction
STACS '93 Proceedings of the 10th Annual Symposium on Theoretical Aspects of Computer Science
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
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Since logical knowledge representation is commonly based on nonclassical formalisms like default logic, autoepistemic logic, or circumscription, it is necessary to perform abductive reasoning from theories of nonclassical logics. In this paper, we investigate how abduction can be performed from theories in default logic. Different modes of abduction are plausible, based on credulous and skeptical default reasoning; they appear useful for different applications such as diagnosis and planning. Moreover, we analyze the complexity of the main abductive reasoning tasks. They are intractable in the general case; we also present known classes of default theories for which abduction is tractable.