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cs.AI2021
A Unifying Bayesian Formulation of Measures of Interpretability in Human-AI
Sarath Sreedharan, Anagha Kulkarni, David E. Smith +1
Existing approaches for generating human-aware agent behaviors have considered different measures of interpretability in isolation. Further, these measures have been studied under…
cs.AI2021
Contrastive Explanations of Plans Through Model Restrictions
Benjamin Krarup, Senka Krivic, Daniele Magazzeni +3
In automated planning, the need for explanations arises when there is a mismatch between a proposed plan and the user's expectation. We frame Explainable AI Planning in the context…