4 citations · 4 across the 1 of their papers we have counts for
2 papers
cs.AI2021★ 4 cited
Identifying Reasoning Flaws in Planning-Based RL Using Tree Explanations
Kin-Ho Lam, Zhengxian Lin, Jed Irvine +5
Enabling humans to identify potential flaws in an agent's decision making is an important Explainable AI application. We consider identifying such flaws in a planning-based deep re…
cs.AI2020
Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kim-Ho Lam, Alan Fern
We investigate a deep reinforcement learning (RL) architecture that supports explaining why a learned agent prefers one action over another. The key idea is to learn action-values…