About this Course
Reinforcement learning (RL) is an area of machine learning concerned with how agents take actions in an environment so as to maximize some notion of cumulative reward. In real word applications, RL is about the optimal control of an autonomous system. Reinforcement learning is considered as one of three machine learning paradigms, alongside supervised learning and unsupervised learning.
The main contents for this level is as follows:
Introduction to Reinforcement Learning
Value and Policy Iteration
Policy Control Problems
Improvements to DQN
Policy Gradient Methods