Decision Making in Large Scale Systems
As taught in: Spring 2004
Tetris game strategies can be analyzed using the value function approximation techniques described in this course -- see lecture session 10. (Illustration courtesy of MIT OpenCourseWare.)
Instructors:
Prof. Daniela Pucci De Farias
MIT Course Number:
2.997
Level:
Graduate
Course Features
Course Description
This course is an introduction to the theory and application of large-scale dynamic programming. Topics include Markov decision processes, dynamic programming algorithms, simulation-based algorithms, theory and algorithms for value function approximation, and policy search methods. The course examines games and applications in areas such as dynamic resource allocation, finance and queueing networks.
*Some translations represent previous versions of courses.
