Cross Domain Policy Transfer with Effect Cycle-Consistency
Ruiqi Zhu,Tianhong Dai,Oya Celiktutan,Ruiqi Zhu,Tianhong Dai,Oya Celiktutan
Training a robotic policy from scratch using deep reinforcement learning methods can be prohibitively expensive due to sample inefficiency. To address this challenge, transferring policies trained in the source domain to the target domain becomes an attractive paradigm. Previous research has typically focused on domains with similar state and action spaces but differing in other aspects. In this p...
