AUTHOR=Najar Anis , Chetouani Mohamed TITLE=Reinforcement Learning With Human Advice: A Survey JOURNAL=Frontiers in Robotics and AI VOLUME=8 YEAR=2021 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2021.584075 DOI=10.3389/frobt.2021.584075 ISSN=2296-9144 ABSTRACT=

In this paper, we provide an overview of the existing methods for integrating human advice into a reinforcement learning process. We first propose a taxonomy of the different forms of advice that can be provided to a learning agent. We then describe the methods that can be used for interpreting advice when its meaning is not determined beforehand. Finally, we review different approaches for integrating advice into the learning process.