rocket-learn is a machine learning framework specifically designed for Rocket League Reinforcement Learning. It works in conjunction with Rocket League, RLGym, and Bakkesmod.
- Reinforcement learning algorithm available out of the box
- Proximal Policy Optimization (PPO)
- extensible format allows new algorithms to be added
- Distributed compute from multiple computers
- Automatic saving of and training against previous agent versions
- Trueskill progress tracking
- Training against Hardcoded/Pretrained Agents
- Training against Humans
- Saving and loading models
- wandb logging
You should use Stable Baselines3 (SB3) to make your bot at first. The hardest parts of building a machine learning bot are
- understanding how to program
- understanding how machine learning works
- choosing good hyperparameters
- choosing good reward functions
- choosing an action parser
- making a statesetter that puts the bot in the best situations
SB3 is a great way to figure out those essential parts. Once you have all of those aspects down, rocket-learn may be a good next step to a better machine learning bot.
If you don't yet have these, rocket-learn will add a large amount of complexity for no added benefit. It's important to remember that high compute and a tough opponent are less important than good fundamentals of ML.
- Get Redis running
Improper Redis setup can leave your computer extremely vulnerable to Bad Guys. We are not responsible for your computer's safety. We assume you know what you are doing.
- Clone the repo
git clone https://github.com/Rolv-Arild/rocket-learn.git
- Start up, in order:
- the Redis server
- the Learner
- the Workers
Look at the examples to get up and running