I recently completed a week-long project to analyze the performance of today's dominant search engines when presented with questions from the famous Jeopardy! game show. The originator of the idea, Stephen Wolfram, used the results in a blog post about the similarities and differences between (where I work), and IBM's intriguing new question-answering system .

If you have already seen one of IBM's television spots, you'll know that in mid-February the system (dubbed "Watson") will compete on a special episode of Jeopardy against the two top Jeopardy champions Ken Jennings and Brad Rutter.

This event is likely to go down as an iconic example of the advance of AI technology into a realm previously reserved for human judgement, a touchstone that is similar in many ways to IBM's successful challenge to the reigning chess world champion with its computer in the late 90s.

For my part, I looked at how well traditional search engines allow one to narrow down the vast corpus of online information to just a page of potential answers to a Jeopardy clue. Not badly, it turns out, although Watson will surely advance the state of the art in text-corpus question answering.

You can find more information on , but I'll reproduce the main bar chart here, along with a fun little word-cloud I made (with the help of ) of the types of entities that occur as the answers to roughly 200k Jeopardy clues. For one thing, it's interesting how close all the major engines are now becoming, as powerful web search increasingly becomes a commodity we take for granted.

( download )

The inventor of , probably also one of the greatest mathematicians of the 20th century, was a rather astounding character named . When he wasn't throwing fabulous parties in Princeton or working on the atomic bomb, Von Neumann was laying some of the groundwork for the science of the late 20th century. Among his many creations was one of the first electronic digital computers, and associated with it the stored-program architecture that still underlies computers today.

A slightly less well known creation of his was the so-called . Something of an alter ego to the digital computer, the cellular automaton is a distributed computational device composed of an array of many simple processors instead of , as in the computer. Unlike Neumann's other ideas, which continued to flourish, cellular automata fell into obscurity until the late 70s, when they experienced something of a renaissance after the of (who happens to be the CEO of the I work for).
More recently, a strange blend of these two ideas has arisen in the guise of rather long-winded . Various academics have what happens when, instead of the disembodied entities of traditional game theory (who one imagines lurking in imaginary war rooms plotting ), the game players are embodied agents situated in physical space on a grid or lattice, interacting with their neighbors.

It turns out that this can make a huge difference to the dynamics of such games. For example, in the traditional game of Prisoner's Dilemma , the only evolutionarily stable strategy (a strategy that a group of agents can play without being undermined by the appearance of mutants in their midst) is for every player to defect -- in other words, a lose-lose situation where everyone mistrusts everyone and we are all unhappy. This is nature red in tooth and claw, pre- Leviathan .

However, when we consider that these agents can be on a grid, and can, so to speak, huddle together for comfort, we notice that "tribes" of co-operators can form that offset the attacks from defectors on all sides by forming many positive relationships amongst themselves (see pictures below, the top panel is where the co-operators (blue) have successfully fought off invaders, in the bottom not so much). In fact, this point gets to the heart of one of the puzzles of evolutionary biology: why altruism exists and how it evolved.

This last result was discovered only recently with the help of computer experiments, and there are sure to be many such discoveries waiting to be made in the field of evolutionary spatial game theory. To this end (yup, all of this post so far has been background -- it links up too beautifully to not mention the history), I've been working on a software library to allow experiments in ESGT to be conducted elegantly and efficiently. To leave you with a taste of what such experiments to look like, here are some videos of the game of Rock Paper Scissors being played on grid (at various 'temperatures', or degrees of randomness):

I'll post more such videos in the future as I do further experiments, and hopefully delve a little more into the details of the science that is going on. If you're interested in the code and seeing some more examples, or even playing around with it yourself if you have a copy of Mathematica , you can visit the project page on GitHub:

Long live spatial game theory!