Explainable AI through the Learning of Arguments

Autor: Jonas Bei, David Pomerenke, Lukas Schreiner, Sepideh Sharbaf, Pieter Collins, Nico Roos

Publikováno v: Maastricht University
Proceedings of BNAIC/BeneLearn 2021: 33rd Benelux Conference on Artificial Intelligence and the 30th Belgian Dutch Conference on Machine Learning BNAIC/BENELEARN, 241-255
STARTPAGE=241;ENDPAGE=255;TITLE=Proceedings of BNAIC/BeneLearn 2021

Learning arguments is highly relevant to the field of explainable artificial intelligence. It is a family of symbolic machine learning techniques that is particularly human-interpretable. These techniques learn a set of arguments as an intermediate r

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