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Approaches to self-explanation and system visibility in the context of application tasks

Published online by Cambridge University Press:  04 August 2010

M. A. Bramer
Affiliation:
University of Portsmouth
G. A. Ringland
Affiliation:
SERC Rutherford Appleton Laboratory. Chilton, Didcot, OXON. 0X11 OQX. United Kingdom.
H. R. Chappel
Affiliation:
SERC Rutherford Appleton Laboratory. Chilton, Didcot, OXON. 0X11 OQX. United Kingdom.
S. C. Lambert
Affiliation:
SERC Rutherford Appleton Laboratory. Chilton, Didcot, OXON. 0X11 OQX. United Kingdom.
M. D. Wilson
Affiliation:
SERC Rutherford Appleton Laboratory. Chilton, Didcot, OXON. 0X11 OQX. United Kingdom.
G. J. Doe
Affiliation:
SERC Rutherford Appleton Laboratory. Chilton, Didcot, OXON. 0X11 OQX. United Kingdom.
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Summary

ABSTRACT

The degree to which users understand and accept advice from Knowledge-Based Systems can be increased through explanation. However, different application tasks and different sets of users place diverse requirements on an explanation component of a Knowledge-Based System. Thus, the degree of portability of explanation components between applications is reduced. This paper discusses the aspects of explanation that change between application tasks and those that are required for any satisfactory explanation. The requirements placed on Knowledge-based Systems resulting from explanatory capabilities raises implications for the structure and contents of the knowledge-base and the visibility of the system. The discussion is illustrated by four Knowledge-Based System projects.

INTRODUCTION

An important feature of knowledge-based systems compared to other information-providing systems is that the knowledge on which they are based is represented explicitly in the system rather than hidden in the design of the system, or represented implicitly in an algorithm. The knowledge can therefore be used not only to solve the problem for which the knowledge-based system was built, but also to show the user what knowledge is used to solve the problem and hence go some way to explain the system's behaviour. However, whilst the explicitness of the knowledge makes it possible to provide some explanatory capability, it does not necessarily mean that the system is capable of producing every explanation required by its users. Some explanations require further reasoning and knowledge to retrieve and act on the knowledge already present in the knowledge-based system.

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Publisher: Cambridge University Press
Print publication year: 1993

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