rlhive 1.0.1

A package to support RL research

Installing | Tutorials | Contributing

RLHive

RLHive is a framework designed to facilitate research in reinforcement learning. It provides the components necessary to run a full RL experiment, for both single agent and multi agent environments. It is designed to be readable and easily extensible, to allow users to quickly run and experiment with their own ideas.

The full documentation and tutorials are available at https://rlhive.readthedocs.io/.

Installing

RLHive is available through pip! For the basic RLHive package, simply run pip install rlhive.

You can also install dependencies necessary for the environments that RLHive comes with by running pip install rlhive[<env_names>] where <env_names> is a comma separated list made up of the following:

• atari
• gym_minigrid
• pettingzoo

In addition to these environments, Minatar and Marlgrid are also supported, but need to be installed separately.

To install Minatar, run pip install MinAtar@git+https://github.com/kenjyoung/MinAtar.git@8b39a18a60248ede15ce70142b557f3897c4e1eb

To install Marlgrid, run pip install marlgrid@https://github.com/kandouss/marlgrid/archive/refs/heads/master.zip

Tutorials

• Creating new agents
• Using DQN/Rainbow Agents
• Using Environments/Creating new Environments
• Configuring your experiments through YAML files and command line
• Loggers and Scheduling
• Registering Custom RLHive Objects
• Using Replay Buffers
• Single/Multi-Agent Runners

Contributing

We'd love for you to contribute your own work to RLHive. Before doing so, please read our contributing guide.