Fast reinforcement learning through the composition of behaviours

Imagine if you had to learn how to chop, peel and stir all over again every time you wanted to learn a new recipe. In many machine learning systems, agents often have to learn entirely from scratch when faced with new challenges. It’s clear, however, that people learn more efficiently than this: they can combine abilities previously learned. In the same way that a finite dictionary of words can be reassembled into sentences of near infinite meanings, people repurpose and re-combine skills they already possess in order to tackle novel challenges.