Explanation in Expert Systems : A Survey

By Johanna D. Moore. 1988

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Citations in the corpus

Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, background): “…and Klein, 2017, 2018; Kass and Finin, 1988; Lacave and Díez, 2002; Lipton, 2016; Miller, 2017; Miller, Howe, and Sonenberg, 2017; Molnar, 2018; Moore and Swartout, 1988; Moulin, Irandoust, Bélanger, and Desbordes, 2002; Nakatsu, 2004; Sørmo, Cassens, and Aamodt, 2005; Swartout, 1987; Swartout…”
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI) (2018, background): “While the term is relatively new, the problem of explainability has existed since the mid-1970s when researchers studied explanation for expert systems [21].”
Expl(AI)n It to Me – Explainable AI and Information Systems Research (2021, background): “…Explainable Artiﬁcial Intelligence (Van Lent et al. 2004; Adadi and Berrada 2018), is steadily increasing, its origins can be traced back to the 1980s where there have already been efforts to explain outputs of Artiﬁcial Intelligence systems of the time (see Moore and Swartout 1988 for a survey).”
Explainable, trustworthy, and ethical machine learning for healthcare: A survey (2021, result): “Although the problem of explaining intelligent algorithms to humans is known since the 1970s, however, the work in this research area slowed down due to advances in ML techniques [34].”
A Review of Explanation and Explanation in Case-Based Reasoning (2003, background): “A common approach to attempt to increase confidence in a system’s output is to include an explanation of the result in the system’s output (Moore and Swartout, 1988).”