GAN-Based Interactive Reinforcement Learning from Demonstration and Human Evaluative Feedback
Jie Huang,Jiangshan Hao,Rongshun Juan,Randy Gomez,Keisuke Nakamura,Guangliang Li,Jie Huang,Jiangshan Hao,Rongshun Juan,Randy Gomez,Keisuke Nakamura,Guangliang Li
Generative adversarial imitation learning (GAIL) — a general model-free imitation learning method, allows robots to directly learn policies from expert trajectories in large environments. However, GAIL shares the limitation of other imitation learning methods that they can seldom surpass the performance of demonstrations. In this paper, to address the limit of GAIL, we propose GAN-based interactiv...
