What is hands-on-rl?

Hands-on Reinforcement Learning is a Chinese-language educational resource that teaches reinforcement learning from the ground up. Reinforcement learning is a branch of machine learning where a program learns to make decisions by trying actions and receiving rewards or penalties based on the results, similar to how a person learns through trial and experience. The repository contains a collection of Jupyter Notebooks, one per chapter, each combining written explanations with runnable code. The series starts from the basic definition of reinforcement learning and works through a range of mainstream algorithms used in the field today. The authors recommend visiting the project's companion website rather than reading the notebooks directly on GitHub, since GitHub's notebook rendering has limitations. The site version provides a better reading experience with the same content. The notebooks are also available for local download and execution. The README includes a note that if you encounter errors running the gym simulation environment, installing a specific older version of that library often fixes the problem. An accompanying video course is available on the Boyu Learning platform and is free for all learners. The content also exists as a printed book sold through major Chinese book retailers. Issues and improvement suggestions are accepted through the standard GitHub issue tracker.