#RL
5 posts
PPO Speedrun
Quickly understand the core ideas and implementation details of the PPO (Proximal Policy Optimization) algorithm, and master this important method in modern reinforcement learning.
A First Look at Actor-Critic Methods
Exploring the Actor-Critic method, which combines the strengths of policy gradients (Actor) and value functions (Critic) for more efficient reinforcement learning.
From DQN to Policy Gradient
Exploring the evolution from value-based methods (DQN) to policy-based methods (Policy Gradient), and understanding the differences and connections between the two.
Reinforcement Learning Basics and Q-Learning
Learning the fundamental concepts of Reinforcement Learning from scratch, and deeply understanding the Q-Learning algorithm and its application in discrete action spaces.
Introduction to Policy Gradient
Learning the fundamental principles and implementation of policy gradient methods, and understanding how to train reinforcement learning agents by directly optimizing the policy.