Dr. Matthew E. Taylor, professor of Artificial Intelligence at WSU, developed a method that allows a "teacher" computer to give advice to a "student" computer in a way that mimics how you might teach a fellow human, except with an algorithm. The trick is in how often the teaching computer gives pointers—too frequently means the student isn't learning, and too sparse makes the learning process slow.

"We designed algorithms for advice giving, and we are trying to figure out when our advice makes the biggest difference,'' Taylor says. With the right timing, the "teacher" machine was able to guide the "student" machine through learning how to play Pac-Man and a modified version of StarCraft—eventually leading to the student machine playing more skillfully than the teacher. It's easy to see how this same process could apply to something like, I don't know, killing all humans.


The implications here are huge. In the future, machine teaching could, for instance, allow outmoded factory robots to teach their replacement equipment, no downtime required. Eventually, the long-term goal is to create robots that can teach humans.

Just, please. Leave the classic videogames for us. When the robots finally do take over, Pac-Man might be the only comfort we have. [Washington State University via ScienceDaily]