  Home robots may come with many sophisticated built-in abilities, however
there will always be a degree of customization needed for each user and
environment. Ideally this should be accomplished through one-shot learning, as
collecting the large number of examples needed for statistical inference is
tedious. A particularly appealing approach is to simply explain to the robot,
via speech, what it should be doing. In this paper we describe the ALIA
cognitive architecture that is able to effectively incorporate user-supplied
advice and prohibitions in this manner. The functioning of the implemented
system on a small robot is illustrated by an associated video.
