Multilayer of ring-structured feedback network for production system processing

Andrew Sohn, Jean Luc Gaudiot

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

It is demonstrated that the ANN (artificial neural network) approach can be applied to problems in artificial intelligence--in particular, to production systems. Among various types of neural networks, the three-layer ring-structured feedback network with three associative memories is considered to suit the problem domain. Characteristics of the production system paradigm are identified, based on which mapping strategies are developed. Two types of representation techniques are studied: local and hierarchical. The local representation can give an O(1) pattern matching time in production systems when an efficient training strategy is used. The hierarchical representation derives features from production systems and constructs a three-dimensional feature space, where a pattern can be uniquely defined by a vector. Simulation results demonstrate that the proposed architecture and mapping strategy can be an efficient solution to the production system paradigm.

Original languageEnglish (US)
Title of host publicationIEEE Int Workshop Tools Artif Intell Archit Lang Algorithms
Editors Anon
PublisherPubl by IEEE
Pages457-464
Number of pages8
ISBN (Print)0818619848
StatePublished - Dec 1 1989
Externally publishedYes
EventIEEE International Workshop on Tools for Artificial Intelligence: Architectures, Languages and Algorithms - Fairfax, VA, USA
Duration: Oct 23 1989Oct 25 1989

Publication series

NameIEEE Int Workshop Tools Artif Intell Archit Lang Algorithms

Other

OtherIEEE International Workshop on Tools for Artificial Intelligence: Architectures, Languages and Algorithms
CityFairfax, VA, USA
Period10/23/8910/25/89

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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