p-94-01        

Issues in Goal-Driven Explanation

David B. Leake

Proceedings of the 1994 AAAI Spring Symposium on Goal-Driven Learning,
pp. 72-79.

When a reasoner explains surprising events for its internal
use, a key motivation for explaining is to perform learning that will
facilitate the achievement of its goals.  Human explainers use a range
of strategies to build explanations, including both internal reasoning
and external information search, and goal-based considerations have a
profound effect on their choices of when and how to pursue
explanations.  However, standard AI models of explanation rely on
goal-neutral use of a single fixed strategy---generally backwards
chaining---to build their explanations.  This paper argues that
explanation should be modeled as a goal-driven learning process for
gathering and transforming information, and discusses the issues
involved in developing an active multi-strategy process for
goal-driven explanation.



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