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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

Keywords

SIPS, semi-intelligent process selector, manufacturing, frame-base reasoning systems

Citation

Nau, D. (1986), Hierarchical Abstraction of Problem-Solving Knowledge, Proceedings of the ASME Winter Annual Meeting, , USA (Accessed April 24, 2024)
Created January 31, 1986, Updated October 12, 2021