These are the exercise files used for Deep Reinforcement Learning for Beginners course.
The course outline can be found in
https://www.tertiarycourses.com.sg/deep-reinforcement-learning-course.html
https://www.tertiarycourses.com.my/deep-reinforcement-learning-course-malaysia.html
Topic 1 Introduction to Reinforcement Learning
- Fundamental Concepts of Reinforcement Learning (RL)
- Types of RL Algorithms
- Applications of RL
- Markov Decision Process (MDP)
Topic 2 OpenAI Gym
- Introduction to OpenAI Gym
- Install OpenAI Gym and Tensorflow
- Try Out OpenAI Gyms
Topic 3 Value Based Q-Learning
- Overview of Value Based Learning
- Value Functions
- Introduction to Q-Learning
- Exploration Strategies
- Implementation of Q-Learning on OpenAI Gym
- Introduction to SARSA
- Implementation of SARSA on OpenAI Gym
Topic 4 Policy Valued Learning
- Overview of Policy Based Learning
- Policy Gradient
- Concept of Advantage Function
- Implementation of Policy Gradient on OpenAI Gym
Topic 5 Overview of Advanced RL Algorithms
- Deep Q Network (DQN)
- Actor-Critic (AC)
- Proximal Policy Gradient (PPO)