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.
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Metadata
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Release files for torchrl-agents 0.4.12
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|---|---|---|---|---|
| torchrl_agents-0.4.12-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 59.4 kB
Release files / torchrl_agents-0.4.12.tar.gz
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