Rutgers University 3 credits 544
Introduction to the basic theory and models of reinforcement learning, the exploration/exploitation model, understanding the e-greedy algorithms, the Gittins indices, posterior sampling, UCB, and optimistic programming methodologies. Software available on public cloud computing platforms are introduced and used.
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