ReAgent
An end-to-end platform for applied reinforcement learning and contextual bandits, originally developed at Facebook for production recommendation systems.
What is ReAgent?
ReAgent is an open-source platform for applied reinforcement learning and decision-making systems, originally developed and used at Facebook. It provides an end-to-end solution for training, evaluating, and serving RL models in production environments, particularly for recommendation systems and optimization tasks where simulators aren't available.
Machine learning engineers and researchers building production reinforcement learning systems, particularly those working on recommendation systems, contextual bandits, or batch RL applications.
Developers choose ReAgent for its comprehensive production-ready workflow, support for safety-focused tools like counterfactual policy evaluation, and its origin as Facebook's internal RL platform designed for real-world applications.
Overview
A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)
Use Cases
Best For
- Building production reinforcement learning systems for recommendation engines
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