Sample Efficiency

The amount of data (environment interactions, demonstrations, or training samples) required to achieve a given level of performance. Sample-efficient algorithms learn faster from less data. In robotics, sample efficiency is crucial because real-world data collection is expensive and slow. Offline RL, model-based RL, data augmentation, and pre-training all improve sample efficiency.