Cloud-Edge Training Architecture for Sim-to-Real Deep Reinforcement Learning
Hongpeng Cao,Mirco Theile,Federico G. Wyrwal,Marco Caccamo,Hongpeng Cao,Mirco Theile,Federico G. Wyrwal,Marco Caccamo
Deep reinforcement learning (DRL) is a promising approach to solve complex control tasks by learning policies through interactions with the environment. However, the training of DRL policies requires large amounts of training experiences, making it impractical to learn the policy directly on physical systems. Sim-to-real approaches leverage simulations to pretrain DRL policies and then deploy them...
