Integrating problem-solving methods into Cyc

Authors:
James Stuart Aitken;Dimitrios Sklavakis
Affiliations:
Artificial Intelligence Applications Institute, Division of Informatics, University of Edinburgh, Edinburgh, Scotland;School of Artificial Intelligence, Division of Informatics, University of Edinburgh, Edinburgh, Scotland
Venue:
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Year:
1999

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Abstract

This paper argues that the reuse of domain knowledge must be complemented by the reuse of problem-solving methods. Problem-solving methods (PSMs) provide a means to structure search, and can provide tractable solutions to reasoning with a very large knowledge base. We show that PSMs can be used in a way which complements large-scale representation techniques, and optimisations such as those for taxonornie reasoning found in Cyc. Our approach illustrates the advantages of task-oriented knowledge modelling and we demonstrate that the resulting ontologies have both task-dependent and task-independent elements. Further, we show how the task ontology can be organised into conceptual levels to reflect knowledge typing principles.