3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.AI2025
Objective Metrics for Human-Subjects Evaluation in Explainable Reinforcement Learning
Balint Gyevnar, Mark Towers
Explanation is a fundamentally human process. Understanding the goal and audience of the explanation is vital, yet existing work on explainable reinforcement learning (XRL) routine…
cs.MA2022★ 1 cited
Deep Reinforcement Learning for Multi-Agent Interaction
Ibrahim H. Ahmed, Cillian Brewitt, Ignacio Carlucho +14
The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Tow…
cs.RO2022★ 3 cited
A Human-Centric Method for Generating Causal Explanations in Natural Language for Autonomous Vehicle Motion Planning
Balint Gyevnar, Massimiliano Tamborski, Cheng Wang +3
Inscrutable AI systems are difficult to trust, especially if they operate in safety-critical settings like autonomous driving. Therefore, there is a need to build transparent and q…