When we learn something new, like a language or musical instrument, we often seek challenges at the edge of our competence--not so hard that we are discouraged, but not so easy that we get bored. This simple intuition, that there is a sweet spot of difficulty, a'Goldilocks zone'1, for motivation and learning is at the heart of modern teaching methods2 and is thought to account for differences in infant attention between more and less learnable stimuli1. In the animal learning literature it is the intuition behind shaping3 and fading4, whereby complex tasks are taught by steadily increasing the difficulty of a training task. It is also observable in the nearly universal'levels' feature in video games, in which the player is encouraged, or even forced, to a higher level of difficulty once a performance criterion has been achieved. Similarly in machine learning, steadily increasing the difficulty of training has proven useful for teaching large scale neural networks in a variety of tasks5,6, where it is known as'Curriculum Learning'7 and'Self-Paced Learning'8.
Nov-12-2019, 12:42:20 GMT