Learning agent architecture for design and manufacturing knowledge on the Web: an extension of enterprise resource planning capabilities

The proliferation of online databases highlights the need for intelligent agents to assist in information retrieval and decision making. A prominent class of applications relates to product design, whose ultimate physical embodiment as a tangible object underscores the utility of employing multimedi...

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Bibliographic Details
Published inIntelligent systems in accounting, finance & management Vol. 8; no. 1; p. 15
Main Author Kim, Steven H
Format Journal Article
LanguageEnglish
Published Chichester Wiley Periodicals Inc 01.03.1999
Subjects
Artificial intelligence
Decision making
Enterprise resource planning
Forecasting techniques
Information retrieval
Information systems
Internet
Manufacturing resource planning
Multimedia
Online data bases
Privacy
Product design
Software
Studies
User needs
World Wide Web
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Summary:The proliferation of online databases highlights the need for intelligent agents to assist in information retrieval and decision making. A prominent class of applications relates to product design, whose ultimate physical embodiment as a tangible object underscores the utility of employing multimedia data structures during the entire lifecycle, from conception and synthesis to production and maintenance. The pertinent multimedia formats cover the gamut from sound and animation to video and virtual reality in addition to conventional text. To this end, intelligent agents can support users ranging from designers to manufacturers, and from salespersons to customers. A competent software agent should possess greater functionality than merely fetch data or broadcast simple information. In particular, an intelligent agent should be able to perform routine tasks autonomously, glean new knowledge from disparate databases, and improve its own performance through experience. This paper examines a number of critical issues behind the development of such agents, formulates a general architecture, and demonstrates the deployment of a learning agent for industrial planning. [PUBLICATION ABSTRACT]
ISSN:1550-1949
2160-0074