Work vs. play

In my office at school I often go back and forth between playing poker and doing research; my friends sometimes joke around about how they are basically the same thing. I usually correct them; while much of my research applies to poker, there is a big difference between when I am playing poker and when I am actually doing research (i.e., working on projects that will lead to papers). It turns out that this is only sort of true and that my friends are kind of right; my poker playing has actually had a substantial and unique impact on my research.

My first main research project in grad school was on an algorithm for computing an approximate Nash equilibrium in 3-player poker endgames. It ended up resulting in two papers so far, and hopefully a journal paper if I can find time to write it up. I got the idea to work on this after playing thousands of poker tournaments; I think it's fair to say that there is a 0% chance I would have come up with this project idea if I didn't play poker myself.

My interest in poker also got me to browse the 2+2 poker forums, which among other things led me to this great book on poker theory. As it turned out, my next main research project involved significantly generalizing the main algorithm used throughout the book. Here is the conference version of that paper, and here is an extended tech report. This project is still in progress, and I've made some significant improvements since those versions.

For both projects I described above, my interest in poker led to the choice of topic; however, the actual research had very little to do with my poker playing. For one of my recent projects, the algorithm I came up with was actually based roughly on the strategy I use when playing. The main idea is to start with a strong, approximate-equilibrium strategy, and deviate from it to take advantage of specific observed weaknesses of opponents. I came up with an algorithm for two-player limit Texas Hold'em based on this reasoning which ended up exploiting weaker players significantly more than the equilibrium strategy did. This seems to be the first real work combing game-theoretic reasoning and opponent modeling in real time. Here is the conference version of the paper.

What is the lesson to take from all of this? Maybe in addition to grades, GRE scores, and recommendations, grad schools should also require applicants to submit relevant game-playing experience:) Seriously though, I do think that people with "nontraditional" backgrounds and experiences can sometimes bring a fresh new perspective to academic problems that people with traditional backgrounds can't. My favorite example is Persi Diaconis, a statistician at Stanford who dropped out of high school at age 14 to become a professional magician.