kh-ryu/RL_Lab

Data Science and Reinforcement Learning

This course covers the basic theory of reinforcement learning and its practices. The course introduces the fundamental algorithmic techniques (model-based, model-free, policy gradients, etc.) of reinforcement learning. The students will be well-versed in both the fundamental theory of RL and the implementation of (deep) RL algorithms.

Lab assignments

In this repository, I will upload my result of each lab assginment.