p-93-01 Focusing Construction and Selection of Abductive Hypotheses David B. Leake Proceedings of the Eleventh International Joint Conference on Artificial Intelligence}, 1993, pp. 24-29. Abstract: Many abductive understanding systems explain novel situations by a chaining process that is neutral to explainer needs beyond generating some plausible explanation for the event being explained. This paper examines the relationship of standard models of abductive understanding to the case-based explanation model. In case-based explanation, construction and selection of abductive hypotheses are focused by specific explanations of prior episodes and by goal-based criteria reflecting current information needs. The case-based method is inspired by observations of human explanation of anomalous events during everyday understanding, and this paper focuses on the method's contributions to the problems of building good explanations in everyday domains. We identify five central issues, compare how those issues are addressed in traditional and case-based explanation models, and discuss motivations for using the case-based approach to facilitate generation of plausible and useful explanations in domains that are complex and imperfectly understood. A postscript file for the full paper is available electronically. To get a copy by anonymous ftp, see ftp://ftp.cs.indiana.edu/pub/leake/README. on the web, open URL ftp://ftp.cs.indiana.edu/pub/leake/INDEX.html.