This paper appears in: Electronic Technology Directions to the Year 2000, 1995. Proceedings.
Publication Date: 23-25 May 1995
On page(s): 18-27
Meeting Date: 05/23/1995 - 05/25/1995
Location: Adelaide, SA, Australia
ISBN: 0-8186-7085-1
References Cited: 17
INSPEC Accession Number: 4957633
Digital Object Identifier: 10.1109/ETD.1995.403493
Current Version Published: 2002-08-06
Abstract
In the last decade or so, expert systems also called
knowledge-based systems have made their way from research laboratories
into the real world. Applications have been, and are continuing to be,
developed in areas as diverse as business, medicine, manufacturing,
defence, astronomy, science and engineering. Such applications perform
tasks that include interpretation, prediction, diagnosis, design,
planning, monitoring, debugging, repairing, instruction and control. The
expert systems are the offshoots of artificial intelligence which is
concerned with using computers to simulate human intelligence in a
limited way. Some researchers define artificial intelligence (AI) as the
science of making machines do things that would require intelligence if
done by men. In the last few decades, AI has spread into major subfields
including expert systems, artificial neural networks, fuzzy systems,
evolutionary computation and chaos theory. Some researchers do not
differentiate between expert systems and knowledge-based systems. The
key issue behind all these developments is the knowledge acquisition,
knowledge representation and knowledge processing
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