Northwestern University 1 credit Electrical Engineering
Fundamentals of Deep Reinforcement Learning starting from its roots in dynamic programming and optimal control, and ending with some of the most popular applications in practice today; basic Q-Learning algorithm and its extensions; deep Q-Learning. Through exercises and a final course project students will gain significant hands-on experience coding up and testing reinforcement systems on a variety of interesting problems. Prerequisites: ELEC_ENG 475-0 and ELEC_ENG 435-0.
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