On the complexity of propositional knowledge base revision, updates, and counterfactuals
Artificial Intelligence
Compilability and compact representations of revision of Horn knowledge bases
ACM Transactions on Computational Logic (TOCL)
Statistical mechanics methods and phase transitions in optimizationproblems
Theoretical Computer Science - Phase transitions in combinatorial problems
Concept Formation and Knowledge Revision
Concept Formation and Knowledge Revision
The Complexity of Iterated Belief Revision
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Essential and redundant rules in Horn knowledge bases
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Weakening conflicting information for iterated revision and knowledge integration
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
Theoretical Computer Science
A continuous–discontinuous second-order transition in the satisfiability of random Horn-SAT formulas
Random Structures & Algorithms
Learning large scale common sense models of everyday life
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Incremental recompilation of knowledge
Journal of Artificial Intelligence Research
Inverse resolution as belief change
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Combinatorial Problems for Horn Clauses
Graph Theory, Computational Intelligence and Thought
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
On approximate horn formula minimization
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
Horn contraction via epistemic entrenchment
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
On the link between partial meet, kernel, and infra contraction and its application to Horn logic
Journal of Artificial Intelligence Research
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Minimal change: Relevance and recovery revisited
Artificial Intelligence
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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Horn-to-Horn belief revision asks for the revision of a Horn knowledge base such that the revised knowledge base is also Horn. Horn knowledge bases are important whenever one is concerned with efficiency--of computing inferences, of knowledge acquisition, etc. Horn-to-Horn belief revision could be of interest, in particular, as a component of any efficient system requiring large commonsense knowledge bases that may need revisions because, for example, new contradictory information is acquired. Recent results on belief revision for general logics show that the existence of a belief contraction operator satisfying the generalized AGM postulates is equivalent to the existence of a complement. Here we provide a first step towards efficient Horn-to-Horn belief revision, by characterizing the existence of a complement of a Horn consequence of a Horn knowledge base. A complement exists if and only if the Horn consequence is not the consequence of a modified knowledge base obtained from the original by an operation called body building. This characterization leads to the efficient construction of a complement whenever it exists.