Study On Bayesian Decision Making Theory And Methods

In this paper,three questions are mainly discussed. First,I developed a new decision making method , named Bayesian multiple objective decision making which can be applied in the problems with many risks. The traditional Bayesian decision making method only takes one risk into account, so it deals with the problems that have many risks inconveniently. The traditional multiple objective decision making method can not use the prior information. The new method that I developed avoids the shortcomings which we talk about. Second, a new method named Bayesian many persons multiple objective decision making method was developed by me. Using it, we can deal with the decision making problem with many risks and in which many persons take part during the process of the decision making. Like the traditional multiple objective decision making method, the traditional many persons multiple objective decision making method also can not use the prior information. Using the method that I propose can fully utilize the prior information. In the two methods which we just talk about, I also give several principles about how to get the last solution. By using the two methods, the scale where Bayesian decision making application is expanded. The third is how to use Bayesian decision making theory to deal with no-linear Bayesian dynamic models. In this section I make the calculation about the no-linear Bayesian dynamic models simple and simultaneously I turn the no-linear Bayesian dynamic forecasting models into a no-linear Bayesian dynamic decision making models. With the aid of the models, we can realize that forecasting and decision making carry on alternately. In fact the process of the decision making in my models is more similar to the process that people make decision in practice.