ABSTRACT
Factories are fascinating test-beds for integrated learning systems. In recent years their sensory capabilities have, in many cases, been advanced and integrated so that data from all over the plant is available in real time over a LAN. Here we discuss how reinforcement learning, and related machine learning methods, can take advantage of this information to learn to improve performance, to adapt to change, and to exploit databases of historical records or similar processes in different plants.
