Propositional lower bounds: Algorithms and complexity

  • Authors:

  • Marco Cadoli;Luigi Palopoli;Francesco Scarcello

  • Affiliations:

  • Dipartimento di Informatica e Sistemistica, Università di Roma “La Sapienza”, Via Salaria 113, I‐00198 Roma, Italy E-mail: cadoli@dis.uniroma1.it;Dipartimento di Elettronica Informatica e Sistemistica, Università della Calabria, I‐87036 Rende (CS), Italy E-mail: {palopoli, scarcello}@deis.unical.it;Dipartimento di Elettronica Informatica e Sistemistica, Università della Calabria, I‐87036 Rende (CS), Italy E-mail: {palopoli, scarcello}@deis.unical.it

  • Venue:
  • Annals of Mathematics and Artificial Intelligence
  • Year:
  • 1999

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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?”