Abstract
Propositional greatest lower bounds (GLBs) are logically‐defined approximations of a knowledge base. They were defined in the context of Knowledge Compilation, a technique developed for addressing high computational cost of logical inference. A GLB allows for polynomial‐time complete on‐line reasoning, although soundness is not guaranteed. In this paper we propose new algorithms for the generation of a GLB. Furthermore, we give precise characterization of the computational complexity of the problem of generating such lower bounds, thus addressing in a formal way the question “how many queries are needed to amortize the overhead of compilation?”
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Cadoli, M., Palopoli, L. & Scarcello, F. Propositional lower bounds: Algorithms and complexity. Annals of Mathematics and Artificial Intelligence 27, 129–148 (1999). https://doi.org/10.1023/A:1018971231561
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DOI: https://doi.org/10.1023/A:1018971231561