Course Description

Course CodeCourse NameCreditsHours
3615053 Deep Reinforcement Learning 3.0 3
Description The goal of this course is to introduce fundamental theories behind deep reinfocement learning and summarize the state-of-the-art research results. We will also teach how to use Python deep learning framework (TensorFlow & PyTorch) and demonstrate how to train software agents to learn different tasks. The content includes: 1.Introduction to Reinforcement Learning 2.Finite Markov Decision Processes 3.Monte Carlo Methods 4.Temporal-Difference Learning 5.Deep Q-Networks (DQN) 6.OpenAI Gym 7.Actor-Critic Methods (A3C & A2C) 8.Trust Regions – TRPO, PPO and ACKTR