Improving Interactive Reinforcement Agent Planning with Human Demonstration

no code implementations • 18 Apr 2019 • Guangliang Li, Randy Gomez, Keisuke Nakamura, Jinying Lin, Qilei Zhang, Bo He

Our results show that learning from demonstration can allow a TAMER agent to learn a roughly optimal policy up to the deepest search and encourage the agent to explore along the optimal path.

reinforcement-learning Reinforcement Learning (RL)

Deep Interactive Reinforcement Learning for Path Following of Autonomous Underwater Vehicle

no code implementations • 10 Jan 2020 • Qilei Zhang, Jinying Lin, Qixin Sha, Bo He, Guangliang Li

In this paper, we proposed a deep interactive reinforcement learning method for path following of AUV by combining the advantages of deep reinforcement learning and interactive RL.

reinforcement-learning Reinforcement Learning (RL)