Sam Austin AI·Jul 24Policy Gradient Methods Explained: REINFORCE Algorithm Step by StepOkay, confession time: when I first heard about policy gradient methods, I thought they were just a fancy way of saying “gradient descent…
Ebad Sayed·May 14MountainCar with Actor-Critic (A2C) — Continuous Actions from ScratchWhat Are We Building?
Dr. Narayan Srinivasa·Jan 29Stable Steps in a Chaotic World: Decoding Proximal Policy OptimizationReinforcement learning is full of beauty and frustration. At its core is a simple promise: an agent learns by acting, failing, adapting —…
Dr. Narayan Srinivasa·Jan 19Credit with Critique: Why Actor–Critic Changes EverythingREINFORCE is a beautiful idea. Strip reinforcement learning down to its essence, and you arrive at something almost disarmingly simple…
Dr. Narayan Srinivasa·Jan 9Credit Without Critics: How REINFORCE Teaches Policies What to DoIn reinforcement learning, progress often comes from asking the same question in slightly different ways — each time under fewer…
