ericyangyu/PPO-for-Beginners
A simple and well styled PPO implementation. Based on my Medium series: https://medium.com/@eyyu/coding-ppo-from-scratch-with-pytorch-part-1-4-613dfc1b14c8.
This project helps machine learning practitioners understand and implement Proximal Policy Optimization (PPO) from scratch using PyTorch. It takes theoretical knowledge of PPO and translates it into a clear, runnable codebase, producing a trained reinforcement learning agent. It's designed for those with some experience in Python and Reinforcement Learning who want to build PPO models.
1,219 stars. No commits in the last 6 months.
Use this if you are an aspiring or junior Reinforcement Learning engineer looking for a highly readable, unembellished PPO implementation to learn from and build upon.
Not ideal if you need a production-ready PPO library with advanced features or if you are completely new to Reinforcement Learning concepts.
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Language
Python
License
MIT
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Last pushed
Oct 01, 2024
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