Empirical evaluation demonstrates rapid filtering of incompatible knowledge-base combinations in automated reasoning systems, highlighting reduced computational overhead for knowledge reuse.
Effective reuse of Knowledge Bases (KBs) often entails the expensive task of identifying plausible KB-PS (Problem Solver) combinations. We propose a novel technique based on Constraint Satisfaction to enable more rapid identification of incompatible KBs, leaving fewer combinations on which to conduct a thorough investigation. In this paper, we describe our investigation process, its tools, and the latest empirical results applied to non-binary problems that demonstrate our relaxation approach is an effective method for plausibility testing.
No takes yet. Share an insight, caveat, or question.
Nordlander et al. (2005) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: