Integrating Top-down and Bottom-up Reasoning in CoLab

Martin Harm, Knut Hinkelmann, Thomas Labisch

DFKI DFKI Documents (D) 92-27 1992.


The knowledge compilation laboratory COLAB integrates declarative knowledge representation formalisms, providing source-to-source and source-to-code compilers of various knowledge types. Its architecture separates taxonomical and assertional knowledge. The assertional component consists of a constraint system and a rule system, which supports bottom-up and top-down reasoning of Horn clauses. Two approaches for forward reasoning have been implemented. The first set-oriented approach uses a ficpoint computation. It allows top-down verification of selected premises. Goal-directed bottom-up reasoning is achieved by a magic-set transformation of the rules with respect to a goal. The second tuple-oriented approach reasons forward to derive the consequences of an explicitly given set of facts. This is achieved by a transformation of the rules to top-down executable Horn clauses. The paper gives an overview of the various forward reasoning approaches, their compilation into an abstract machine and their integration into the COLAB shell.

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence