Title :
A Decision Assistant Based on Evidential Reasoning
Author :
Wu, Qing-Xiang ; Bell, David ; Guan, Ji-wen ; Khokhar, Rh ; Huang, Xi ; Zhong, Shao-chun
Author_Institution :
Sch. of Phys. & OptoElectron. Technol., Fujian Normal Univ., Fuzhou
Abstract :
The evidence theory provides an important reasoning mechanism in artificial intelligence, and it has been applied to complex systems to handle uncertainty reasoning. Using a set of easy-to-use interfaces, we have designed a desktop decision assistant system based on the evidence theory. Through the easy-to-use interfaces, expert knowledge and opinions or political arguments can be input to the system easily. An incremental evidence combination algorithm is embedded in a reasoning module in the system. Based on the evidential reasoning module, the system can carry out uncertainty reasoning efficiently. Therefore, the system can be applied to enhance human capability to make decisions in daily life, business, or political arguments. As the easy-to-use interfaces are designed, the decision assistant can make decisions in different situations with only a few keyboard clicks. A couple of examples of applications are also demonstrated in this paper
Keywords :
case-based reasoning; decision making; human computer interaction; uncertainty handling; artificial intelligence; decision assistant system; easy-to-use interface; evidence theory; evidential reasoning mechanism; incremental evidence combination algorithm; uncertainty reasoning; Application software; Artificial intelligence; Bayesian methods; Computer science; Cybernetics; Decision making; Educational institutions; Humans; Keyboards; Machine learning; Physics; Uncertainty; Decision Assistant; decision making; evidential reasoning; uncertainty reasoning;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.259130