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Explainable Multi-Agent Reinforcement Learning for Temporal Queries

By Kayla Boggess and others at
LogoUniversity of Virginia, Charlottesville
and
LogoUniversity of Virginia
As multi-agent reinforcement learning (MARL) systems are increasingly deployed throughout society, it is imperative yet challenging for users to understand the emergent behaviors of MARL agents in complex environments. This work presents an approach for generating policy-level contrastive explanations for MARL to answer a temporal user query, which specifies a... Show more
May 17, 2023
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Explainable Multi-Agent Reinforcement Learning for Temporal Queries
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