PROGRAMMING BY EXAMPLE: THE HUMAN FACE OF AI
Date
1991-04-01
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Abstract
Interactive computer users often find themselves repeatedly performing
similar tasks that could be acquired automatically from a teacher.
This paper presents principles derived from experience in creating
four prototype learners: for technical drawing, text editing, office
tasks, and robot assembly.
A teaching metaphor (a) enables the user to demonstrate a task by
performing it manually, (b) helps to explain the learner's limited
capabilities in terms of a persona, and (c) allows users to attribute
intentionality. Tasks are represented procedurally, and augmented
with constraints. Suitable mechanisms for attention focusing are
necessary in order to control inductive search. Hidden features of a
task should be made explicit so that the learner need not entertain,
and search, all possible missing steps.
Key features of the interaction are formalized as "felicity conditions"
that help a learner by guaranteeing more explicit, consistent information
in demonstrations. Systems that are programmed by human instruction can
capitalize on appropriate interactive methods to boost the computational
limitations of inductive inference.
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Computer Science