AUTONOMY, INTELLIGENCE, AND INSTRUCTABILITY

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.