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Model-preference default theories

Journal Article journal-article Artificial Intelligence

Abstract

Most formal theories of default inference have very poor computational properties, and are easily shown to be intractable, or worse, undecidable. We are therefore investigating limited but efficiently computable theories of default reasoning. This paper defines systems of propositional model-preference defaults, which provide a model-theoretic account of default inference with exceptions. The most general system of model-preference defaults is decidable but still intractable. Inspired by the very good (linear) complexity of propositional Horn theories, we consider systems of Horn defaults. Surprisingly, finding a most preferred model in even this very limited system is shown to be NP-hard. Tractability can be achieved in two ways: by eliminating the “specificity ordering” among default rules and by restricting our attention to systems of acyclic Horn defaults. These acyclic theories can encode acyclic defeasible inheritance hiearchies, but are more general.

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Context

Venue
Artificial Intelligence
Archive span
1970-2026
Indexed papers
3976
Paper id
915778930939058572
v2026.09.13