2025
Delayed Dynamic Model Scheduled Reinforcement Learning With Time-Varying Delays for Robotic Control
RA-L 2025
Reinforcement learning (RL) typically presupposes instantaneous agent-environment interactions, but in real-world scenarios such as robotic control, overlooking observation delays can significantly impair performance. While existing studies consider stationary, known delays, real-world applications