DAgger (Dataset Aggregation)

DAgger (Dataset Aggregation) is a learning method for training autonomous systems, like robots or self-driving cars. It involves initially letting the system learn from human experts, then progressively collecting data from the system's own actions. This data includes cases where the system might make mistakes, and the correct actions are provided by an expert. By repeatedly updating its knowledge with this combined data, the system becomes more accurate and reliable over time. Essentially, DAgger helps the system learn from experience while continuously improving by correcting its errors with expert guidance.