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Dissertation Information for David Browder Leake

NAME:
- David Browder Leake

DEGREE:
- Ph.D.

DISCIPLINE:
- Computer Science

SCHOOL:
- Yale University (USA) (1990)

ADVISORS:
- None

COMMITTEE MEMBERS:
- None

MPACT Status: Incomplete - Not_Inspected

Title: Evaluating explanations

Abstract: "Explanation-based learning (EBL) is a powerful method for category formation. However, the value of EBL to a system's performance depends critically on two factors that have been neglected in EBL research. First, the system needs criteria for deciding what needs to be explained. Second, since many candidate explanations can be generated for a given anomaly, and not all of them are reasonable, it needs to be able to recognize and reject bad explanations.

This thesis presents a theory of problem detection and characterization for explanations--both for standard explanations generated during routine understanding, and for more complex explanations built to account for novel events. During routine understanding, stereotype-based tests are used to identify anomalies efficiently. Anomalies signal gaps in an understander's knowledge, and those gaps must be filled by further explanation. The anomalies are described in an indexing vocabulary which can be used to focus search for possible explanations. Candidate explanations are evaluated both for plausibility, using the anomaly detection process, and for their usefulness to overarching system tasks.

Thus problem detection is presented as a dynamic process that depends strongly on the explainer's goals. In this theory, evaluation criteria reflect context, the explainer's knowledge, and its needs for specific information--what the explainer knows, and what it needs to find out. The theory is implemented in ACCEPTER, a program that detects anomalies in stories, and identifies problems in alternative explanations for those anomalies."

MPACT Scores for David Browder Leake

A = 0
C = 3
A+C = 3
T = 0
G = 0
W = 0
TD = 0
TA = 0
calculated 2014-02-09 17:04:37

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