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A novel architecture based on fuzzy cognitive maps and holonic systems for decision making in a cooperative context

A novel architecture based on fuzzy cognitive maps and holonic systems for decision making in a... Ensuring consistency and good decision making is one of the most topical problems in an information system; it becomes more difficult in a cooperative context. In this paper, we propose an architecture based on fuzzy cognitive maps (FCM) tool and holonic multi-agent paradigm that enhance the decision making process in cooperative information system (CIS). Furthermore, the concept of ontolgy is used for semantically enrich our architecture. We modelled each sub-CIS by a holonic agents where everyone used a FCM for a more precise analysis of complex dynamic system decisions. This group will try to make a collective decision to solve any given distributed problem. To put our approach into practice, we considered road safety field to see how to educate people in order to reduce the fatal accidents number. Finally, we validated our proposition through experiments to show how it improves the decision making process in a cooperative context. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Information and Decision Sciences Inderscience Publishers

A novel architecture based on fuzzy cognitive maps and holonic systems for decision making in a cooperative context

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1756-7017
eISSN
1756-7025
DOI
10.1504/IJIDS.2019.101992
Publisher site
See Article on Publisher Site

Abstract

Ensuring consistency and good decision making is one of the most topical problems in an information system; it becomes more difficult in a cooperative context. In this paper, we propose an architecture based on fuzzy cognitive maps (FCM) tool and holonic multi-agent paradigm that enhance the decision making process in cooperative information system (CIS). Furthermore, the concept of ontolgy is used for semantically enrich our architecture. We modelled each sub-CIS by a holonic agents where everyone used a FCM for a more precise analysis of complex dynamic system decisions. This group will try to make a collective decision to solve any given distributed problem. To put our approach into practice, we considered road safety field to see how to educate people in order to reduce the fatal accidents number. Finally, we validated our proposition through experiments to show how it improves the decision making process in a cooperative context.

Journal

International Journal of Information and Decision SciencesInderscience Publishers

Published: Jan 1, 2019

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