Code to generate interpretable explanations in cyber-physical systems.
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Updated
May 14, 2025 - Jupyter Notebook
Code to generate interpretable explanations in cyber-physical systems.
Code for "In search of 'normality': producing relevant counterfactual explanations for complex behaviors" (ACSOS 2026)
Code for actual causes filtering based on relevance metrics.
Code for presenting and evaluating search algorithms for actual causes identification
Code for the python model `actualcauses` that implements algorithms for HP-causes identification.
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