The explanation game: a formal framework for interpretable machine learning.

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation(s) for a given algorithmic prediction. Throug...

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Detalles Bibliográficos

Publicado en:	Synthese Vol. 198; no. 10; pp. 9211 - 9243
Autores principales:	Watson, David S., Floridi, Luciano
Formato:	Artículo
Publicado:	Springer Nature Oct2021
Materias:	Machine learning Decision theory Statistical learning Polynomial time algorithms Explanation
Acceso en línea:	Ver este registro en EBSCOhost