Language features for flexible handling of exceptions in information systems
ACM Transactions on Database Systems (TODS)
Artificial Intelligence
A catalog of complexity classes
Handbook of theoretical computer science (vol. A)
The complexity of finite functions
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Propositional knowledge base revision and minimal change
Artificial Intelligence
Model checking vs. theorem proving: a manifesto
Artificial intelligence and mathematical theory of computation
On the complexity of propositional knowledge base revision, updates, and counterfactuals
Artificial Intelligence
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
Belief revision and update: complexity of model checking
Journal of Computer and System Sciences
On the semantics of updates in databases
PODS '83 Proceedings of the 2nd ACM SIGACT-SIGMOD symposium on Principles of database systems
The comparative linguistics of knowledge representation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Redundancy in logic I: CNF propositional formulae
Artificial Intelligence
Horn complements: towards horn-to-horn belief revision
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Redundancy in logic I: CNF propositional formulae
Artificial Intelligence
Next steps in propositional horn contraction
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Horn Belief Change: A Contraction Core
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Belief revision within fragments of propositional logic
Journal of Computer and System Sciences
Horn clause contraction functions
Journal of Artificial Intelligence Research
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Several methods have been proposed as an attempt to deal with dynamically changing scenarios. From a computational point of view, different formalisms have different computational properties. In this article we consider knowledge bases represented as sets of Horn clauses. The importance of this case is twofold: first, inference is polynomial, thus tractable; second, Horn clauses represents causal relations between facts, thus they are of great practical importance, although not all propositional knowledge bases can be represented in Horn form. The complexity of Horn revision is still high, and in some cases coincides with the complexity of the general (non-Horn) case. We analyze the complexity of belief revision from the point of view of the compilation [Cadoli et al. 1999]: we study the possibility of reducing the complexity by allowing a (possibly expensive) preprocessing of part of the input of the problem. Extending the work of Cadoli et al.[1996], we consider the problem of compact representation of revision in the Horn case, i.e., given a knowledge base T and an update P (both represented by Horn clauses) decide whether T * P, the result of the revision, can be represented with a propositional formula whose size is polynomial in the size of T and P. We give this representation for all formalisms for which it exists, and we show that the existence of a compact representation is related to the possibility of decreasing the complexity of a formalism via a proprocessing.