# Additional Readings [[additional-readings]]

These are **optional readings** if you want to go deeper.

## PPO Explained

- [Towards Delivering a Coherent Self-Contained Explanation of Proximal Policy Optimization by Daniel Bick](https://fse.studenttheses.ub.rug.nl/25709/1/mAI_2021_BickD.pdf)
- [What is the way to understand Proximal Policy Optimization Algorithm in RL?](https://stackoverflow.com/questions/46422845/what-is-the-way-to-understand-proximal-policy-optimization-algorithm-in-rl)
- [Foundations of Deep RL Series, L4 TRPO and PPO by Pieter Abbeel](https://youtu.be/KjWF8VIMGiY)
- [OpenAI PPO Blogpost](https://openai.com/blog/openai-baselines-ppo/)
- [Spinning Up RL PPO](https://spinningup.openai.com/en/latest/algorithms/ppo.html)
- [Paper Proximal Policy Optimization Algorithms](https://arxiv.org/abs/1707.06347)

## PPO Implementation details

- [The 37 Implementation Details of Proximal Policy Optimization](https://iclr-blog-track.github.io/2022/03/25/ppo-implementation-details/)
- [Part 1 of 3 — Proximal Policy Optimization Implementation: 11 Core Implementation Details](https://www.youtube.com/watch?v=MEt6rrxH8W4)

## Importance Sampling

- [Importance Sampling Explained](https://youtu.be/C3p2wI4RAi8)