RLlib is an open-source reinforcement learning (RL) library built on top of Ray. It enables scalable training of RL agents with support for a wide variety of algorithms, environments, and deep learning frameworks like PyTorch and TensorFlow. RLlib simplifies both research experimentation and production deployment by providing a unified, modular API for RL development.

Features of RLlib:

• Includes implementations of popular RL algorithms such as PPO, DQN, A3C, and IMPALA.
• Built for scalability, supporting distributed training across CPUs, GPUs, and clusters.
• Compatible with both PyTorch and TensorFlow backends.
• Provides easy integration with OpenAI Gym and custom environments.
• Flexible and modular design, allowing customization of policies, models, and training workflows.
• Open-source and actively maintained, widely used in research and production applications.

To check the installed version of RLlib on Ubuntu 24.04, run these commands in your environment:

$ sudo su
$ sudo apt update
$source /opt/rllib/venv/bin/activate
$ python -c "import ray; print(ray.__version__)"

Disclaimer: RLlib is released under the Apache 2.0 License and maintained by the Ray community. Users are responsible for correct usage in their specific applications. The developers are not responsible for any consequences arising from its use. Always refer to the official RLlib documentation for the most accurate and up-to-date information.