Integrating Problem-Solving Methods into CYC

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 taxonomic 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 reect knowledge typing principles. 1 Introduction Developing reusable ontologies which specify the structure and content of domain knowledge has become a central problem in the construction of large and scalable knowledge based systems. For example, a key step in KBS construction usin...

Cite

Text

Aitken and Sklavakis. "Integrating Problem-Solving Methods into CYC." International Joint Conference on Artificial Intelligence, 1999.

Markdown

[Aitken and Sklavakis. "Integrating Problem-Solving Methods into CYC." International Joint Conference on Artificial Intelligence, 1999.](https://mlanthology.org/ijcai/1999/aitken1999ijcai-integrating/)

BibTeX

@inproceedings{aitken1999ijcai-integrating,
  title     = {{Integrating Problem-Solving Methods into CYC}},
  author    = {Aitken, James S. and Sklavakis, Dimitrios},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1999},
  pages     = {627-633},
  url       = {https://mlanthology.org/ijcai/1999/aitken1999ijcai-integrating/}
}