Nau, D.
(1986),
Hierarchical Abstraction of Problem-Solving Knowledge, Proceedings of the ASME Winter Annual Meeting, , USA
(Accessed October 31, 2024)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Hierarchical Abstraction of Problem-Solving Knowledge
Published
Author(s)
D Nau
Abstract
In most frame-based reasoning systems, the data manipulated by the system is represented using frames, and the problem-solving knowledge used to manipulate this data consists of rules. However, rules are not always the best way to represent problem-solving knowledge. This paper describes an alternative way to represent problem-solving knowledge called hierarchical knowledge clustering. Hierarchical knowledge clustering has been implemented in a system called SIPS (Semi-Intelligent Process Selector), which plans what machining processes to use in manufacturing metal parts. The paper describes the approach to knowledge representation and problem solving used in SIPS, and compares and contrasts this approach to other work.Proceedings Title
Proceedings of the ASME Winter Annual Meeting
Conference Location
, USA
Pub Type
Conferences
Keywords
SIPS, semi-intelligent process selector, manufacturing, frame-base reasoning systems
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.
Created January 31, 1986, Updated October 12, 2021