Analysis of Application Status of Bayesian Decision

Abstract

There are many applications of Bayesian decision theory in computer science and mathematical modeling. Because of how it works, the algorithm can evaluate possible outcomes and choose a course of action. Decisions are made in the face of ambiguity and incomplete information in every area of human activity. When making a choice, it is common for the outcomes and their worth to the decision maker to rely on factors outside their control. Bayesian decision theory is devoted to solving these sorts of decision-making difficulties. Using Bayesian decision theory has benefited engineering, economics, business, public policy, and even AI. Examining recent literature in the field, this study delves into how Bayesian decision theory might be used for tasks including mistake detection, risk assessment, and route planning. The study’s findings demonstrate the value and utility of using Bayesian decision theory, and the authors hope that its presentation will stimulate the use of a similar approach in the future.