Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment: a case study
✍ Scribed by Xudong Luo; Chengqi Zhang; Ho-fung Leung
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 620 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0888-613X
No coin nor oath required. For personal study only.
✦ Synopsis
The issue of information sharing and exchanging is one of the most important issues in the areas of arti®cial intelligence and knowledge-based systems, 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 wellknown 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, dierent ones can handle dierent 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