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Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment : a case study

Luo, Xudong, Zhang, Chengqi and Leung, Ho-fung 2001, Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment : a case study, International journal of approximate reasoning, vol. 27, no. 1, pp. 27-59.

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Title Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment : a case study
Author(s) Luo, Xudong
Zhang, Chengqi
Leung, Ho-fung
Journal name International journal of approximate reasoning
Volume number 27
Issue number 1
Start page 27
End page 59
Total pages 32 p.
Publisher Elsevier Inc.
Place of publication New York, N.Y.
Publication date 2001-06
ISSN 0888-613X
Summary The issue of information sharing and exchanging is one of the most important issues in the areas of artificial intelligence and knowledge-based systems (KBSs), or even in the broader areas of computer and information technology. This paper deals with a special case of this issue by carrying out a case study of information sharing between two well-known heterogeneous uncertain reasoning models: the certainty factor model and the subjective Bayesian method. More precisely, this paper discovers a family of exactly isomorphic transformations between these two uncertain reasoning models. More interestingly, among isomorphic transformation functions in this family, different ones can handle different degrees to which a domain expert is positive or negative when performing such a transformation task. The direct motivation of the investigation lies in a realistic consideration. In the past, expert systems exploited mainly these two models to deal with uncertainties. In other words, a lot of stand-alone expert systems which use the two uncertain reasoning models are available. If there is a reasonable transformation mechanism between these two uncertain reasoning models, we can use the Internet to couple these pre-existing expert systems together so that the integrated systems are able to exchange and share useful information with each other, thereby improving their performance through cooperation. Also, the issue of transformation between heterogeneous uncertain reasoning models is significant in the research area of multi-agent systems because different agents in a multi-agent system could employ different expert systems with heterogeneous uncertain reasonings for their action selections and the information sharing and exchanging is unavoidable between different agents. In addition, we make clear the relationship between the certainty factor model and probability theory.
Notes External
Language eng
Field of Research 080101 Adaptive Agents and Intelligent Robotics
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30008419

Document type: Journal Article
Collection: School of Information Technology
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