IEMS 469: Dynamic Programming VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Basic knowledge of probability (random variables, expectation, conditional probability), optimization (gradient), ...

In this course we introduce the fundamentals of Deep Reinforcement Learning from scratch starting from its roots in Dynamic Programming and optimal control, and ending with some of the most popular ...

Our results suggest new modeling paradigms for dynamic robust optimization, and our proofs, which bring together ideas from three areas of optimization typically studied separately—robust optimization ...

Kelly J. Bryant, James W. Mjelde, Ronald D. Lacewell, An Intraseasonal Dynamic Optimization Model to Allocate Irrigation Water between Crops, American Journal of ...