Understanding REINFORCE Policy Gradients From Scratch
fpedregosa · x · 2026-07-13
The author has launched a new blog series aimed at understanding modern reinforcement learning algorithms from the ground up.
The first part focuses on the classic REINFORCE estimator, covering:
- How to derive an unbiased policy gradient without differentiating through the environment;
- Why this estimator suffers from high variance;
- Using foundational derivations to help readers build intuition for subsequent RL algorithms.
This is a fundamental but highly practical technical read, ideal for those looking to systematically understand the mechanics of RL.
Related event: Understanding the REINFORCE Estimator from Scratch(2 posts)→
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