Texas A&M University 3 credits CSCE
Fundamentals of formalizing reinforce learning (RL) problems such as Markov Decision Process as well as various techniques and approaches for optimizing the agent's behavior given such problems; exploration of basic concepts and approaches in deep neural networks; overview of state-of-the-art algorithms that integrate deep learning with reinforcement learning; basics of reinforcement learning as well as deep reinforcement learning. Prerequisites: Graduate classification.
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