On the TIRES project (http://daly.axiom-developer.org/cmu/book.pdf) we used Scone (http://www.cs.cmu.edu/~sef/scone/), a knowledge representation system as the core structure. Rules based on OPS5 (http://repository.cmu.edu/cgi/viewcontent.cgi?article=3430&c...) were used to do planning.

Scone concepts were linked to machine learning for two tasks, recognition (e.g. giving grounding to the concept 'wrench' as a recognizable object) and actions (e.g. giving grounding to concepts like tighten as a series of actions).

So ML was an "interface" for recognition and "compiled knowledge" where the system knew how to perform certain actions without any consultation with the rest of the knowledge (similar to how you can recognize and type words without thinking).