Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

The Autonomous Learning Library: A PyTorch Library for Building Reinforcement Learning Agents



The Autonomous Learning Library: A PyTorch Library for Building Reinforcement Learning Agents

The autonomous-learning-library is an object-oriented deep reinforcement learning (DRL) library for PyTorch. The goal of the library is to provide the necessary components for quickly building and evaluating novel reinforcement learning agents, as well as providing high-quality reference implementations of modern DRL algorithms. The full documentation can be found at the following URL: https://autonomous-learning-library.readthedocs.io.

Use Cases

There is no use cases for this tool yet.

Would you like to submit a use case for this tool?

If you have used this tool, we would love to know more about your experience.

Add use case
Partnership on AI

Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.