Continual Learning

Continual learning, also known as lifelong learning, refers to the ability of a machine learning model to learn and adapt continuously over time. Unlike traditional models that are trained on a fixed dataset, continual learning systems can incorporate new information without forgetting previously learned knowledge. This characteristic is particularly important in dynamic environments where data evolves, allowing models to remain relevant and effective. Common use cases include online learning applications, adaptive robotics, and personalized recommendation systems, where models must adjust to new user behaviors or preferences.