PaperNova
Reinforcement Learning
2017
INTERMEDIATE

Proximal Policy Optimization Algorithms

John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov · 2017

PPO. A clipped-surrogate policy-gradient method that balances stability and simplicity — the default RL algorithm behind RLHF and most modern agents.

Start guided workbook →Read original paperPDF

What you'll get

  • Outline: a plain-English breakdown of the paper's core idea, prerequisites, and the concepts you'll need to implement it.
  • Exercises: five to ten hands-on tasks, each with a concept card, a prompt, a starter code stub, and a collapsible reference solution.
  • Runnable notebook: a single .ipynb you can download and open in Jupyter or VS Code to work through every exercise.
  • Extensions: suggested follow-up experiments so you don't stop at a faithful reimplementation.