Shaping Progressive Net of Reinforcement Learning for Policy Transfer with Human Evaluative Feedback
Rongshun Juan,Jie Huang,Randy Gomez,Keisuke Nakamura,Qixin Sha,Bo He,Guangliang Li,Rongshun Juan,Jie Huang,Randy Gomez,Keisuke Nakamura,Qixin Sha,Bo He,Guangliang Li
Deep reinforcement learning has achieved significant success in many fields, but will confront sampling efficiency and safety problems when applying to robot control in the real world. Sim-to-real transfer learning was proposed to make use of samples in the simulation and overcome the gap between simulation and real world. In this paper, we focus on improving Progressive Neural Network — an effect...
