contextual-bandits

A form of machine learning that balances exploration and exploitation in dynamic environments.

Contextual bandits extend traditional bandit problems by incorporating context, allowing for more informed decision-making. In this framework, the algorithm learns to select actions based on the current context to maximize rewards. This approach is particularly useful in online advertising and personalized recommendations, where user preferences can vary widely.