CSCI 385 - Economics and Computation

FC NSMA QFR

4 credits
Many important computational platforms intermediate collective decision making or the distribution of resources. Consequently, understanding these algorithmic systems requires an approach informed by economic theory. On the other hand, analyses of economic systems often benefit from an algorithmic perspective. This theoretical course explores how tools from game theory and economics can improve the design of computational systems, and how algorithmic concepts such as worst-case approximation and computational complexity can improve the design and analysis of markets and institutions. Students will both learn new mathematical skills on regular problem sets and understand current research in the area by reading papers. Economics majors taking this course will receive credit for a 300-level ECON elective.
Prerequisites & Notes: CSCI 280 or consent of instructor.