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cs.AI2025
Integrating Counterfactual Simulations with Language Models for Explaining Multi-Agent Behaviour
Bálint Gyevnár, Christopher G. Lucas, Stefano V. Albrecht +1
Autonomous multi-agent systems (MAS) are useful for automating complex tasks but raise trust concerns due to risks such as miscoordination or goal misalignment. Explainability is v…
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…