A logical framework for default reasoning
Artificial Intelligence
Quantification in autoepistemic logic
Fundamenta Informaticae - Special issue: logics for artificial intelligence
Proceedings of the second international workshop on Logic programming and non-monotonic reasoning
A comparative study of open default theories
Artificial Intelligence
A note on the stable model semantics for logic programs
Artificial Intelligence
Foundations of Logic Programming
Foundations of Logic Programming
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We compare two approaches to the meaning of a free variable x in an open default α(x): Mβ1(x),..., Mβm(x)/γ(x). The first treats x as a metavariable for the ground terms of the underlying theory, whereas the second threats it as a "name" of arbitrary elements of the theory universe. We show that, for normal default theories, under the domain closure assumption, the two approaches are equivalent. In the general case, the approaches are equivalent in the presence of both the domain closure assumption and the unique name assumption.