Enhanced Maintenance and Explanation of Expert Systems Through Explicit Models of Their Development

By Robert Neches, William R. Swartout, Johanna D. Moore. 1984

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Reuben Binns
2. Yiyi Tao
3. Michael Veale
4. Yiling Jia
5. Nan Wang
6. M. V. Kleek
7. Hongning Wang
8. Bernard Moulin

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, neutral): “…1990a, 1990b; Kass and Finin, 1988; Langlotz and Shortliffe, 1989; McKeown and Swartout, 1987; Merrill, 1987; Moore and Swartout, 1988, 1990, 1991, Neches, Swartout, and Moore, 1985a, 1985b; Scott, Clancey, Davis, and Shortliffe, 1977; Scott, Clancey, Davis, and Shortliffe, 1984; Shortliffe,…”
• 'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions (2018, background): “Explanation facilities could be further augmented by explicitly modeling the knowledge engineering and design process and revealing information about them to end-users [50].”
• Explanation and Argumentation Capabilities:Towards the Creation of More Persuasive Agents (2002, background): “Critiquing systems provide a fertile ground for argumentation given that critical discussion is a prototype of argumentative discourse.”
• Explanations in knowledge systems: design for explainable expert systems (1991, background): “( 8 ) A simple variable is named by a symbol.”
• Planning Text for Advisory Dialogues: Capturing Intentional and Rhetorical Information (1993, methodology): “We describe PEA’s text planner in Section 5.)”
• The FacT: Taming Latent Factor Models for Explainability with Factorization Trees (2019, background): “sk of recommendation learning, there is still no guarantee on the fidelity of provided explanations. The idea of providing rule-based explanations was popularized in the development of expert systems [15, 36]. For example, MYCIN [31], a rule-based reasoning system, provides explanations by translati”
• Explaining and justifying recommendations in an agriculture decision support system (1994, background): “SimPLE provides significantly (P Moulin and Beckie, 1993 ).”