Parametric Connectives in Disjunctive Logic Programming
  Disjunctive Logic Programming (\DLP) is an advanced formalism for Knowledge
Representation and Reasoning (KRR). \DLP is very expressive in a precise
mathematical sense: it allows to express every property of finite structures
that is decidable in the complexity class $\SigmaP{2}$ ($\NP^{\NP}$).
Importantly, the \DLP encodings are often simple and natural.
  In this paper, we single out some limitations of \DLP for KRR, which cannot
naturally express problems where the size of the disjunction is not known ``a
priori'' (like N-Coloring), but it is part of the input. To overcome these
limitations, we further enhance the knowledge modelling abilities of \DLP, by
extending this language by {\em Parametric Connectives (OR and AND)}. These
connectives allow us to represent compactly the disjunction/conjunction of a
set of atoms having a given property. We formally define the semantics of the
new language, named $DLP^{\bigvee,\bigwedge}$ and we show the usefulness of the
new constructs on relevant knowledge-based problems. We address implementation
issues and discuss related works.
