Computer search algorithms can be very powerful. The problem is most people outside of technology just don’t get it. It can be hard to explain what it is and how they work without an example non-technical can relate to, and that is what Randy Olson has managed to do with his “Where’s Waldo?” examples. His work is based on the traveling salesman problem that has been around for many years.
As I found myself unexpectedly snowed in this weekend, I decided to take on a weekend project for fun. While searching for something to catch my fancy, I ran across an old Slate article claiming that they found a foolproof strategy for finding Waldo in the classic “Where’s Waldo?” book series. Now, I’m no Waldo-spotting expert, but even I could tell that the strategy they proposed there is far from perfect.
That’s when I decided what my weekend project would be: I was going to pull out every machine learning trick in my tool box to compute the optimal search strategy for finding Waldo. I was going to crush Slate’s supposed foolproof strategy and carve a trail of defeated Waldo-searchers in my wake.
“But Randy, don’t you have better things to work on? You know, curing cancer, solving world hunger… ANYTHING else?”, a sane person would have said at that point.
Too bad that sane person wasn’t around.