A Learning Process Using SVMs for Multi-agents Decision Classification
Yanshan Xiao, Feiqi Deng, Bo Liu, Shouqiang Liu, Dan Luo, Guohua Liang · 2008
In order to resolve decision classification problem in multiple agents system, this paper first introduces the architecture of multiple agents system. It then proposes a support vector machines based assessment approach, which has the ability to learn the rules form previous assessment results from domain experts. Finally, the experiment are conducted on the artificially dataset to illustrate how the proposed works, and the results show the proposed method has effective learning ability for decision classification problems.