The Mirror Agent Model: A Bayesian Architecture for Interpretable Agent Behavior

Explainable and Transparent AI and Multi-Agent Systems(2022)

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摘要
In this paper we illustrate a novel architecture generating interpretable behavior and explanations. We refer to this architecture as the Mirror Agent Model because it defines the observer model, that is the target of explicit and implicit communications, as a mirror of the agent’s. With the goal of providing a general understanding of this work, we firstly show prior relevant results addressing the informative communication of agents intentions and the production of legible behavior. In the second part of the paper we furnish the architecture with novel capabilities for explanations through off-the-shelf saliency methods, followed by preliminary qualitative results.
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关键词
Interpretability, Explainability, Bayesian networks, Mirror Agent Model
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