Multi-armed bandits
This feature is for Early Access Program customers only
Multi-armed bandits are available only to members of LaunchDarkly’s Early Access Program (EAP). If you want access to this feature, join the EAP.
Overview
This section contains documentation on multi-armed bandits, which are a type of experiment that use a decision-making algorithm that dynamically allocates traffic to the best-performing variation of a flag based on a metric you choose.
Unlike traditional A/B experiments, which split traffic between variations and waits for performance results, multi-armed bandits continuously evaluate variation performance and automatically shift traffic toward the best performing variation. Multi-armed bandits are useful when fast feedback loops are important, such as optimizing calls to action, pricing strategies, or onboarding flows.
To learn how to create and read the results for multi-armed bandits, read Creating multi-armed bandits and Multi-armed bandit results.