Computational morality: a process model of belief conflict and resolution for story understanding

By John F. Reeves, Michael G. Dyer. 1991

How researchers see this paper

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

Explaining Explanations: An Overview of Interpretability of Machine Learning (2018, background): “In John Reeves’ thesis [79], he created the THUNDER program to read stories, construct character summaries, infer beliefs, and understand conﬂict and resolution.”
Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning (2018, background): “In John Reeves’ thesis [79], he created the THUNDER program to read stories, construct character summaries, infer beliefs, and understand conﬂict and resolution.”
Understanding script-based stories using commonsense reasoning (2004, unknown): “…systems have been built (Charniak, 1972; Cullingford, 1978; Wilensky, 1978; Lebowitz, 1980; Schank and Riesbeck, 1981; Dyer, 1983; Dolan, 1989; Norvig, 1989; Reeves, 1991; Miikkulainen, 1993; Hobbs et al., 1993; Schank, Kass, and Riesbeck, 1994; Shapiro and Rapaport, 1995; Narayanan, 1997).”