torchrl-agents 0.4.12

Object-oriented RL agents based on torchrl.

TorchRL Agents

TorchRL Agents is a Python package that provides object-oriented reinforcement learning (RL) agents built on top of PyTorch and TorchRL.

Object-Oriented Design

At the core of this package is the Agent abstract base class, which defines a structured interface for RL agents. The Agent class provides a blueprint that other classes can subclass to implement specific RL algorithms. This design ensures consistency and reusability across different agents.

Key Features of the Agent Class:

• Abstract Methods: Enforces the implementation of essential functionalities, such as processing batches and defining policies.
• Serialization: Supports saving and loading agent configurations and weights, enabling easy training and deployment.
• Modularity: Allows for easy extension and customization by subclassing.

By subclassing the Agent class, you can implement various RL algorithms while adhering to a consistent structure.

Installation

pip install torchrl-agents

Examples

See torchrl-examples for some examples where agents are trained on benchmark environments.

License

This project is licensed under the MIT License. See the LICENSE file for details.