Study on the Structure and Behavioral Choice of IDs Model
The complicated decision making problem is one of the important components for the study on the system of artificial intelligence area.This thesis,based on the Bayesian technology and decision-making theory,is going to optimize the traditional IDs model and improve the ability of expression of the model.Firstly,the structure decomposition method is given to divide the IDs into two parts,which are probability network structure and utility function structure.Secondly,a new MDL evaluation standard is put forward to reduce the dependence on statistics of the traditional MDL evaluation standard and based on the new standard to propose to use the PS-EM in the model choice of probability network structure; and also by using the sum of individual utility function instead of the joint utility function to create the BP neural network to study the utility function structure of the IDs.The experimental result shows the method mentioned above is effective.
Complex System IDs structural choice Behavior choice
Zhangyani
Department of Computer Science,Qiannan Normal College for Nationalities,Duyun,Guizhou,china,558000
国际会议
杭州
英文
1854-1857
2013-03-22（万方平台首次上网日期，不代表论文的发表时间）