AIMay 22, 2020
Reinforcement learning with human advice: a survey
arXiv:2005.11016v266 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental survey paper for researchers in reinforcement learning and human-AI interaction.
The paper surveys methods for integrating human advice into reinforcement learning, proposing a taxonomy of advice forms and reviewing interpretation and integration approaches.
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.