Identifying Reasoning Flaws in Planning-Based RL Using Tree Explanations

no code implementations • 28 Sep 2021 • Kin-Ho Lam, Zhengxian Lin, Jed Irvine, Jonathan Dodge, Zeyad T Shureih, Roli Khanna, Minsuk Kahng, Alan Fern

We describe a user interface and case study, where a small group of AI experts and developers attempt to identify reasoning flaws due to inaccurate agent learning.

Decision Making Reinforcement Learning (RL)