Study of the Bayesian Networks

摘要：

A Bayesian network is a graphical model that finds probabilistic relationships among rubles of the system. Bayesian networks pass evidence (data) between nodes and use the expectations from the world model, they can be considered as bi-directional learning systems. In this paper, we provide a detailed definition of Bayesian networks and related theorems. The chain rule theorem is introduced to do the necessary calculations in Bayesian networks. We provide theoretical and historical details on evidential reasoning using the chain rule. Then we explore some questions about the relationship between Bayesian Networks and the functionality of a human brain as our last topic in Bayesian networks. Finally, we introduce influence diagrams method to convert beliefs of an agent into actions.

作者: CAO Yonghui

作者单位: School of Economics & Management Henan Institute of Science and Technology Xinxiang, China

会议类型: 国际会议

会议名称: 2010 International Conference on E-Health Networking,Digital Ecosystems and Techonlogies(2010电子健康网络、数字生态系统和技术国际会议 EDT 2010)

会议地点: 深圳

会议语种:英文

页码: 172-174

在线出版日期: 2010-04-17（万方平台首次上网日期，不代表论文的发表时间）