3 citations · 5 across the 3 of their papers we have counts for
4 papers · 1 filter
How to Measure Human-AI Prediction Accuracy in Explainable AI Systems
Sujay Koujalgi, Andrew Anderson, Iyadunni Adenuga +8
Assessing an AI system's behavior-particularly in Explainable AI Systems-is sometimes done empirically, by measuring people's abilities to predict the agent's next move-but how to…
Explaining Reinforcement Learning to Mere Mortals: An Empirical Study
Andrew Anderson, Jonathan Dodge, Amrita Sadarangani +6
We present a user study to investigate the impact of explanations on non-experts' understanding of reinforcement learning (RL) agents. We investigate both a common RL visualization…
Toward Foraging for Understanding of StarCraft Agents: An Empirical Study
Sean Penney, Jonathan Dodge, Claudia Hilderbrand +3
Assessing and understanding intelligent agents is a difficult task for users that lack an AI background. A relatively new area, called "Explainable AI," is emerging to help address…
How the Experts Do It: Assessing and Explaining Agent Behaviors in Real-Time Strategy Games
Jonathan Dodge, Sean Penney, Claudia Hilderbrand +2
How should an AI-based explanation system explain an agent's complex behavior to ordinary end users who have no background in AI? Answering this question is an active research area…