A Learning-by-Metaphor Human-Machine System

One of the outstanding problems facing designers of expert systems pertains to the capture of human expertise for replay by the system. The scaling of such expert or knowledge-based systems implies a capability for natural language situational entry as well as a meta-rule based system for reasoning...

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Bibliographic Details
Main Author: Rubin, S.H.
Format: Conference Proceeding
Language:English
Subjects:
Cybernetics
Data structures
Expert systems
Hardware
Humans
Information technology
Knowledge based systems
Man machine systems
Natural languages
Switches
Online Access:Request full text
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Description
Summary:One of the outstanding problems facing designers of expert systems pertains to the capture of human expertise for replay by the system. The scaling of such expert or knowledge-based systems implies a capability for natural language situational entry as well as a meta-rule based system for reasoning by analogy. The former capability provides for the semantic normalization of natural language, while the latter capability employs metaphor to expand the derived rule base -thereby enabling it to fail softly.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2006.384833