The Impact of Dataset Quality on Imitation Learning Performance

This chapter examines the importance of high-quality datasets in imitation learning, focusing on how Voice of Customer scores reflect their effectiveness. It highlights the contrast between human-curated datasets and those generated through autonomous exploration, while showcasing an experiment that demonstrates the positive impact of filtering low-quality data on model training.