Why Horn formulas matter in computer science: initial structures and generic examples
Journal of Computer and System Sciences
Structure identification in relational data
Artificial Intelligence - Special volume on constraint-based reasoning
Horn approximations of empirical data
Artificial Intelligence
Interior and exterior functions of Boolean functions
Discrete Applied Mathematics
Artificial Intelligence
Defaults and relevance in model-based reasoning
Artificial Intelligence - Special issue on relevance
Computing intersections of horn theories for reasoning with models
Artificial Intelligence
On Horn Envelopes and Hypergraph Transversals
ISAAC '93 Proceedings of the 4th International Symposium on Algorithms and Computation
Interior and exterior functions of positive Boolean functions
Discrete Applied Mathematics
Knowledge Representation and Reasoning
Knowledge Representation and Reasoning
On computing all abductive explanations from a propositional Horn theory
Journal of the ACM (JACM)
Knowledge compilation using horn approximations
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Reasoning with characteristic models
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
| Hi-index | 0.00 |
In this article, we investigate deductive inference for interiors and exteriors of Horn knowledge bases, where interiors and exteriors were introduced by Makino and Ibaraki [1996] to study stability properties of knowledge bases. We present a linear time algorithm for deduction for interiors and show that deduction is coNP-complete for exteriors. Under model-based representation, we show that the deduction problem for interiors is NP-complete while the one for exteriors is coNP-complete. As for Horn envelopes of exteriors, we show that it is linearly solvable under model-based representation, while it is coNP-complete under formula-based representation. We also discuss polynomially solvable cases for all the intractable problems.