Tetris game strategies can be analyzed using the value function approximation techniques described in this course -- see lecture session 10. (Illustration courtesy of OCW.)
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.
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