Behavioral psychologists have long used mazes to study memory and learning; their subjects, mostly rats and mice.

Now researchers are beginning to use the same approach to test an entirely new kind of subject—the latest breed of artificial intelligence machine. They have started by putting these machines through their paces in mazes created in the online world of Minecraft.

Mazes have a long history in behavioral psychology. At the beginning of the 20th century, scientists became interested in the ability of rats and mice to learn and remember. In particular, they began to study learning mechanisms such as reinforcement learning.

The maze became the standard workhorse for this kind of work. Researchers would devise a complex labyrinth, place some kind of reward at the center, and then set a rat loose inside and see how quickly it solved the puzzle.

Psychologists quickly discovered that rats learned rapidly and could find their way even with various sensory impairments such as being blinded, deafened, or having their whiskers plucked.

But the complexity of early mazes meant that experiments were hard to compare. So eventually psychologists settled on simple mazes in the shape of Ts or Ys, for example, that could easily be reproduced in any lab.

That helped show how rats learn, that genes can determine how quickly rats solve puzzles, and so on. In recent years, computer scientists have even developed virtual reality mazes in which the rats are held stationary and forced to look at a screen while standing on top of a kind of trackball that moves as they walk or run. In this way, the rat advances through the virtual maze.

Now Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, and Honglak

Lee at the University of Michigan have begun experimenting with an entirely new kind of maze to test the cognitive skills of an entirely new kind of being. The new mazes are constructed in Minecraft, a 3-D world in which players use textured cubes to build almost anything. Creating a simple maze is trivial here.

But the beings Oh and co are testing are even more exotic—they are artificial intelligence machines. However, while these machines learn easily in ideal environments, they have difficulty in real world situations where objects can be partially obscured, where vision and movement have to be carefully coordinated to succeed and the resulting reward often delayed.