Under certain conditions, expectational and distributional distributions show no significant difference, particularly in simpler settings. However, as complexity increases with deep networks, distributional methods can provide advantages, though they may also lead to worse performance in some cases. Mark's exploration into these methods led to innovative concepts like adversarial value functions, highlighting the need for a deeper understanding of distributional approaches.
