Search Results for author: Guangliang Li

Found 5 papers, 0 papers with code

Facial Feedback for Reinforcement Learning: A Case Study and Offline Analysis Using the TAMER Framework

no code implementations23 Jan 2020 Guangliang Li, Hamdi Dibeklioğlu, Shimon Whiteson, Hayley Hung

Interactive reinforcement learning provides a way for agents to learn to solve tasks from evaluative feedback provided by a human user.


Deep Interactive Reinforcement Learning for Path Following of Autonomous Underwater Vehicle

no code implementations10 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.


Improving Interactive Reinforcement Agent Planning with Human Demonstration

no code implementations18 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.


Learning Shaping Strategies in Human-in-the-loop Interactive Reinforcement Learning

no code implementations10 Nov 2018 Chao Yu, Tianpei Yang, Wenxuan Zhu, Dongxu Wang, Guangliang Li

Providing reinforcement learning agents with informationally rich human knowledge can dramatically improve various aspects of learning.


Cannot find the paper you are looking for? You can Submit a new open access paper.