Abstract
Instructable systems constitute an important, useful, and practically
realizable step towards fully autonomous ones. In many applications
people will not want machines to be self-motivated, but they will want
to teach them new jobs. The user interface must permit the teacher to
guide the system through tasks. The system employs samples of behavior
so gathered to drive an inductive process of concept learning. Learning
becomes intractable unless the teacher fulfils certain felicity
conditions. The real world frequently constitutes a competitive learning
environment, and instructable systems may have to guard against their
knowledge and skills being corrupted by incorrect or deliberately
misleading teachers. Experimental prototypes of two instructable
systems are presented, one for verbally editing robot movements, the
other for automating office tasks. These examples show the potential
utility of approaching autonomy via instructability; the next steps are
to extend the power of their learning mechanisms, and to render them
robust.
Notes
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