Semantical considerations on nonmonotonic logic
Artificial Intelligence
Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
A logic to reason about likelihood
Artificial Intelligence
On the relation between default and autoepistemic logic
Artificial Intelligence
A logical framework for default reasoning
Artificial Intelligence
Likelihood, probability, and knowledge
Computational Intelligence
Nonmonotonicity and the scope of reasoning
Nonmonotonicity and the scope of reasoning
What the lottery paradox tells us about default reasoning
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Equality and Domain Closure in First-Order Databases
Journal of the ACM (JACM)
Reasoning with Incomplete Information
Reasoning with Incomplete Information
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Relating default logic and circumscription
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Some properties of plausible reasoning
UAI'91 Proceedings of the Seventh conference on Uncertainty in Artificial Intelligence
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Existing formalisms for default reasoning capture some aspects of the nonmonotonicity of human commonsense reasoning. However, Perlis has shown that one of these formalisms, circumscription, is subject to certain counterintuitive limitations. Kraus and Perlis suggested a partial solution, but significant problems remain. In this paper, we observe that the unfortunate limitations of circumscription are even broader than Perlis originally pointed out. Moreover, these problems are not confined to circumscription; they appear to be endemic in current nonmonotonic reasoning formalisms. We develop a much more general solution than that of Kraus and Perlis, involving restricting the scope of nonmonotonic reasoning, and show that it remedies these problems in a variety of formalisms.