  We present a case study of artificial intelligence techniques applied to the
control of production printing equipment. Like many other real-world
applications, this complex domain requires high-speed autonomous
decision-making and robust continual operation. To our knowledge, this work
represents the first successful industrial application of embedded
domain-independent temporal planning. Our system handles execution failures and
multi-objective preferences. At its heart is an on-line algorithm that combines
techniques from state-space planning and partial-order scheduling. We suggest
that this general architecture may prove useful in other applications as more
intelligent systems operate in continual, on-line settings. Our system has been
used to drive several commercial prototypes and has enabled a new product
architecture for our industrial partner. When compared with state-of-the-art
off-line planners, our system is hundreds of times faster and often finds
better plans. Our experience demonstrates that domain-independent AI planning
based on heuristic search can flexibly handle time, resources, replanning, and
multiple objectives in a high-speed practical application without requiring
hand-coded control knowledge.
