I have had the idea of the agent inferring its own background knowledge through observations of the conditions throughout the state and I always figured that this sort of learning already existed somewhere in machine learning.
I have found that it does in fact exist, and is known as association mining. The question is, can association mining tackle streams, variable number of attributes, and generality measures? I somehow doubt the standard association miners in Weka can, so I should instead ask Bernhard about the best one for my purposes and use it as a baseline.
It can tackle generality (if fiddled with appropriately). Such a form of learning/mining is known as multi-level association mining.