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AgileRL

AgileRL provides an open-source framework for reinforcement learning that enhances training speed by up to 10 times through RLOps, supporting both single-agent and multi-agent environments. The platform utilizes evolutionary hyperparameter optimization and distributed training to enable efficient convergence on optimal performance, addressing the challenges of slow training times and complex task management in AI development.

London, United Kingdom · HQ
Founded 20238700+ followers
  • Artificial Intelligence
  • Developer Tools
  • Software Only
Updated 2 days ago

Funding

Raised to date

$2.1MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

1 founder

Mikita Shchutski

Staff ML Engineer (IC6) / Alumni

Product

Problem

Developing reinforcement learning (RL) models is often hindered by slow training times and the complexities of managing various tasks, particularly in hyperparameter optimization and distributed training environments. This can significantly delay the development and deployment of effective AI solutions.

Solution

AgileRL offers an open-source framework designed to accelerate reinforcement learning training through RLOps, supporting both single-agent and multi-agent environments. The framework leverages evolutionary hyperparameter optimization to automatically converge on optimal performance within a single training run. It also facilitates distributed training, enabling users to fully utilize their compute resources, including multi-GPU setups, for both online and offline reinforcement learning.

Target Audience

The primary audience includes AI developers and researchers seeking to streamline and accelerate the development of reinforcement learning models for various applications.

Features

  • Open-source framework for reinforcement learning with RLOps
  • Supports single-agent and multi-agent environments
  • Evolutionary hyperparameter optimization for automatic convergence
  • Distributed training capabilities with multi-GPU support
  • Hierarchical Skills wrapper for breaking down complex tasks into learnable sub-tasks
This profile is AI-generated and may contain inaccuracies.