This course consists of two sections: decision analysis and games.
The first half of this course is an application-oriented course on decision making. We will emphasize the use of dynamic decision methods in theory and practice, especially when uncertainties and multiple decision makers are issues. These methods are widely used and covered in other courses, including decision analysis, stochastic optimization methods, and game theory. However, none of the previous courses emphasize the dynamic interaction between decision-makers and between decisions in different time periods. Different from other courses in decision making, this course will focus on the multiple period, multiple decision maker decision problems. We will also emphasize on the modeling of uncertainties in multi-period decision-making problems. Applications considered in this course include supply chain coordination, revenue management, and technology management. However, the topics discussed also have wide applications to other financial and economic systems.
The second half of the course covers the topics of games application on industry and the course is designed to help students connect game theory with practices in issues of supply chains, industrial economics, or some related topics in decentralized systems, where individual entrepreneurs have their own profit functions and often are unwilling to reveal their own information to each other or the public. In this course we will study the interactions between multiple players (decision makers). Such problems arise frequently in supply chain applications. The interaction of a firm with its competitors, customers and suppliers can be modeled as a game, and hence, our main tool of analysis in this course will be Game Theory. Course goals will be accomplished through lectures, homework, readings and case studies.