State-adaptive policy regularization (SAPPS) for smooth control in continuous-control reinforcement learning, with simulation and real-world experiments.
-
Updated
Feb 23, 2026 - Python
State-adaptive policy regularization (SAPPS) for smooth control in continuous-control reinforcement learning, with simulation and real-world experiments.
Physics-driven hydroelectric dam RL environment — Torricelli hydraulics, diurnal pricing & monsoon surge. Built for Meta × Scaler OpenEnv Hackathon.
Wavefront-sensorless adaptive optics using action-regularized reinforcement learning for optical satellite communication, with simulation environments and reproducible experiments accompanying the Optica Open preprint.
Add a description, image, and links to the continuous-control-rl topic page so that developers can more easily learn about it.
To associate your repository with the continuous-control-rl topic, visit your repo's landing page and select "manage topics."