Rethinking ValueDice: Does It Really Improve Performance?

Understand

Since the introduction of GAIL, adversarial imitation learning (AIL) methods attract lots of research interests.

• Among these methods, ValueDice has achieved significant improvements: it beats the classical approach Behavioral Cloning (BC) under the offline setting, and it requires fewer interactions than GAIL under the online setting.
• Are these improvements benefited from more advanced algorithm designs? We answer this question by the following conclusions.
• First, we show that ValueDice could reduce to BC under the offline setting.