Reinforcement Learning Course
Function Approximation
RL Part 5: From tables to parameterized value functions.
Reinforcement Learning Course
A collection of 6 posts
Reinforcement Learning Course
Model-Free Learning
RL Part 4: Learning value functions and policies without a model. Monte Carlo methods, TD(0), SARSA, Q-learning, and the bias-variance bridge between them.
Reinforcement Learning Course
Bellman Equations and Dynamic Programming
RL Part 3: Bellman expectation and optimality equations, policy iteration, value iteration, and why dynamic programming needs a model.
Reinforcement Learning Course
Markov Decision Processes and Value Functions
RL Part 2: Markov decision processes, returns, policies, and value functions.
Reinforcement Learning Course
Foundations of Reinforcement Learning
RL Part 1: Agents, environments, rewards, and why RL is different from supervised learning.
Reinforcement Learning Course
Reinforcement Learning Course
A series of technical deep dives on Reinforcement Learning that covers fundamentals and background, the classical techniques, MDPs, Bellman equations, deep RL methods, how RL is used to train modern language models, agentic RL, and much more.
