Structural complexity 1
Is intractability of nonmonotonic reasoning a real drawback?
Artificial Intelligence
On compact representations of propositional circumscription
Theoretical Computer Science
The size of a revised knowledge base
Artificial Intelligence
Compilability and compact representations of revision of Horn knowledge bases
ACM Transactions on Computational Logic (TOCL)
Monotonic reductions, representative equivalence, and compilation of intractable problems
Journal of the ACM (JACM)
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Preprocessing of intractable problems
Information and Computation
Space efficiency of propositional knowledge representation formalisms
Journal of Artificial Intelligence Research
The comparative linguistics of knowledge representation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
IEEE Transactions on Computers
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Compilability is a measure of how effectively compilation (or preprocessing) can be applied to knowledge bases specified in a particular knowledge representation formalism; the aim of compilation is to allow for efficient, on-line query processing. A theory of compilability has been established for organizing knowledge representation formalisms according to a scheme of "compilability classes", and bears strong analogies to the classical theory of complexity, which permits the organization of computational problems according to complexity classes. We develop a novel theory of compilability, called parameterized compilability, which incorporates the notion of parameterization as used in parameterized complexity and permits for refined analysis of compilability.