3 papers
cs.AI2026
M2-PALE: A Framework for Explaining Multi-Agent MCTS--Minimax Hybrids via Process Mining and LLMs
Yiyu Qian, Liyuan Zhao, Tim Miller
Monte-Carlo Tree Search (MCTS) is a fundamental sampling-based search algorithm widely used for online planning in sequential decision-making domains. Despite its success in drivin…
cs.HC2026
Same Performance, Hidden Bias: Evaluating Hypothesis- and Recommendation-Driven AI
Michaela Benk, Tim Miller
The HCI community commonly evaluates decision support systems based on whether they improve task performance or promote appropriate user reliance. In this work, we look beyond deci…
cs.AI2024
Towards Explainable Goal Recognition Using Weight of Evidence (WoE): A Human-Centered Approach
Abeer Alshehri, Amal Abdulrahman, Hajar Alamri +2
Goal recognition (GR) involves inferring an agent's unobserved goal from a sequence of observations. This is a critical problem in AI with diverse applications. Traditionally, GR h…