2026
Enhancing Control Policy Smoothness by Aligning Actions with Predictions from Preceding States
AAAI 2026technical
Deep reinforcement learning has proven to be a powerful approach to solving control tasks, but its characteristic high‑frequency oscillations make it difficult to apply in real‑world environments. While prior methods have addressed action oscillations via architectural or loss-based methods, the lat