Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions

Understand

Deep generative models (DGMs) have demonstrated great success across various domains, particularly in generating texts, images, and videos using models trained from offline data.

• Similarly, data-driven decision-making and robotic control also necessitate learning a generator function from the offline data to serve as the strategy or policy.
• In this case, applying deep generative models in offline policy learning exhibits great potential, and numerous studies have explored in this direction.
• However, this field still lacks a comprehensive review and so developments of different branches are relatively independent.