-
-
Courses
Find courses by:
Collections
Cross-Disciplinary Topic Lists
Translated Courses
-
About
-
Donate
-
Featured Sites
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.)
Prof. Daniela Pucci De Farias
2.997
Spring 2004
Graduate
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.
MIT OpenCourseWare makes the materials used in the teaching of almost all of MIT's subjects available on the Web, free of charge. With more than 2,000 courses available, OCW is delivering on the promise of open sharing of knowledge.
© 2001–2012
Massachusetts Institute of Technology
Your use of the MIT OpenCourseWare site and materials is subject to our Creative Commons License and other terms of use.
