  We relate behavior composition, a synthesis task studied in AI, to
supervisory control theory from the discrete event systems field. In
particular, we show that realizing (i.e., implementing) a target behavior
module (e.g., a house surveillance system) by suitably coordinating a
collection of available behaviors (e.g., automatic blinds, doors, lights,
cameras, etc.) amounts to imposing a supervisor onto a special discrete event
system. Such a link allows us to leverage on the solid foundations and
extensive work on discrete event systems, including borrowing tools and ideas
from that field. As evidence of that we show how simple it is to introduce
preferences in the mapped framework.
