<?xml version="1.0" standalone="yes"?>
<Paper uid="P94-1035">
  <Title>An Attributive Logic of Set Descriptions Set Operations</Title>
  <Section position="11" start_page="260" end_page="260" type="relat">
    <SectionTitle>
7 Related Work
</SectionTitle>
    <Paragraph position="0"> Feature logics and concept languages suchas KL-ONE are closely related family of languages \[Nebel and Smolka, 1991\]. The principal difference being that feature logics interpret attributive labels as functional binary relations while concept languages interpret them as just binary relations. However the integration of concept languages with feature logics has been problematic due to the fact the while path equations do not lead to increased computational complexity in feature logic the addition of rolevalue-maps (which are the relational analog of path equations) in concept languages causes undecidability \[Schmidt-Schant3, 1989\]. This blocks a straight-forward integration of a variable-free concept language such as ALC \[Schmidt-SchanB and Smolka, 1991\] with a variable-free feature logic \[Smolka, 1991\].</Paragraph>
    <Paragraph position="1"> In \[Manandhax, 1993\] the addition of variables, feature symbols and set descriptions to ALC is investigated providing an alternative method for integrating concept languages and feature logics. It is shown that set descriptions can be translated into the so called &amp;quot;number restrictions&amp;quot; available within concept languages such as BACK \[yon Luck et al., 1987\]. However, the propositionally complete languages ALV and ALS investigated in \[Manandhar, 1993\] are PSPACE-hard languages which do not support set operations.</Paragraph>
    <Paragraph position="2"> The work described in this paper describes yet another unexplored dimension for concept languages - that of a restricted concept language with variables, feature symbols, set descriptions and set operations for which the consistency checking problem is within the complexity class NP.</Paragraph>
  </Section>
class="xml-element"></Paper>