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Parallelism in knowledge-based machines

Published online by Cambridge University Press:  07 July 2009

Apostolos N. Refenes
Apostolos N. Refenes
Affiliation:
Department of Computer Science, University College London, UK
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Abstract

The application area of knowledge-based expert systems is currently providing the main stimulus for developing powerful, parallel computer architectures. Languages for programming knowledge-based applications divide into four broad classes: Functional languages (e.g. LISP), Logic languages (e.g. PROLOG), Rule-Based languages (e.g. OPS5), and, what we refer to as self-organizing networks (e.g. BOLTZMANN machines).

Despite their many differences, a common problem for all language classes and their supporting machine architectures is parallelism: how to de-compose a single computation into a number of parallel tasks that can be distributed across an ensemble of processors. The aim of this paper is to review the four types of language for programming knowledge-based expert systems, and their supporting parallel machine architectures. In doing so we analyze the concepts and relationships that exist between the programming languages and their parallel machine architectures in terms of their strengths and limitations for exploiting parallelization.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 4 , Issue 1 , March 1989 , pp. 53 - 71
Copyright
Copyright © Cambridge University Press 1989

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