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20202025
most citedExplainable Multi-Agent Reinforcement Learning for Temporal Queries

1 citations · 4 across the 7 of their papers we have counts for

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cs.AI2025

Explaining Decentralized Multi-Agent Reinforcement Learning Policies

Kayla Boggess, Sarit Kraus, Lu Feng

Multi-Agent Reinforcement Learning (MARL) has gained significant interest in recent years, enabling sequential decision-making across multiple agents in various domains. However, m…

cs.AI2025

Evaluating Human Trust in LLM-Based Planners: A Preliminary Study

Shenghui Chen, Yunhao Yang, Kayla Boggess +3

Large Language Models (LLMs) are increasingly used for planning tasks, offering unique capabilities not found in classical planners such as generating explanations and iterative re…