Alberto L. Sangiovanni-Vincentelli

Equivariant Ensembles and Regularization for Reinforcement Learning in Map-based Path Planning

In reinforcement learning (RL), exploiting environmental symmetries can significantly enhance efficiency, robustness, and performance. However, ensuring that the deep RL policy and value networks are respectively equivariant and invariant to exploit these symmetries is a substantial challenge. Relat