I took a few minutes away from studying today to attend a talk in the business school at Northwestern given by Bruce Bueno de Mesquita (BdM). I first read about him a few years ago in an article in GOOD Magazine.  He’s an important guy, I guess.  He has a wikipedia page, a TED talk, was on the Daily Show, and has published a few books and papers. By modern standards he fits those qualifications for importance. He’s also a professor at NYU and consults various “top-secret” high level government entities (I roll my eyes when people talk about that kind of stuff). I was able to find a few interesting papers [1][2] he had published previously but it looks like he only really works with mass-market writing and consulting these days.

Some of what I study here is game theory, in fact, the theme of my next quarter is game theory: two courses on game theory and one that will probably be about game theory on networks.  I knew a little bit about his work beforehand and I know various game theoretic models so I was hoping he would talk more quantitatively.  Unfortunately, any slide with numbers or equations on it, he quickly skipped in lieu of talking about his quantitative ability and giving his thoughts on international politics.  Not that it was not interesting, he is a very captivating speaker and I find international politics interesting.

However, I left the talk asking myself if I learned anything really new or valuable from the talk. I don’t think I did. I left with the following take-aways:

• BdM and his team are good at making predictions about global international conflict.   They are right 90% of the time. Some journalists and the government says so.
• He uses game theory to do this.
• Many of his models are super complicated and he gets hired by Uncle Sam and big corporations alike.
• He has talented undergrads working with some of his models.

I was hoping that he would share more insight into how those who do theory (like me) can apply models to the real world. How can we leverage cooperative game theory and economics to make claims about international politics? What kinds of models does he use? How does he use the work of guys like Myerson?  Does he use any algorithmic game theory? If so, what algorithms are important? As students and those who study game theory, what kinds of research should we consider doing?

There were some very pre-eminant game theorists in the audience and I was disappointed they didn’t ask any questions at the end. Rather, he had a couple softball questions about his thoughts on current global situations.  I regret not asking questions like those above.  Lesson learned.

Hello blog-world. I haven’t blogged in a while. I’ve been working on some pretty cool research, including a Mathematica implementation of the Metropolis Algorithm for social network (ERGM) analysis. I will add it to the site when I complete it.  You should be excited.  Anyway, for the sake of record-keeping, here are the courses I am looking forward to taking next term here at Northwestern.

• Applied Math 495 – Dynamical Processes on Networks – This is an applied math course, so I expect it to be pretty challenging. However, it is on my research specialty, social networks.  I’m taking this course with an undergrad friend of mine who really knows his stuff, so this should be a great course. It’s taught by Dirk Brockman, who has done some cool research.
• Economics 410-3 – This is the third series in the dreaded PhD level economics sequence. The theme for next quarter is game theory.  The theme this semester was general equilibrium theory. So, yeah. I’m happy to be moving on to game theory, something I’m more comfortable with.  The course is taught by Michael Whinston, the guy that co-wrote the infamous Mas-Collell (MWG) textbook.  I’m looking forward to this course but I’m also terrified.
• Computer Science 495 – Algorithmic Mechanism Design – One of my co-advisers, Jason Hartline is teaching this course. His research speciality is mechanism design and his last few papers have been focused around bayesian and prior-free settings. I expect this course to be rigorous mathematically but have lots of applied uses in research, especially since I started at NU wanting to do computational mechanism design work.
• I’m also auditing a course taught by Uri Wilinsky on NetLogo, a really cool agent-based modeling software that I used for a while when I was at Michigan. The course is a 300-level, so if the workload isn’t too bad, I may take it for credit. Otherwise, I will just audit it and work at getting better at the software which can be used in a lot of simulation settings, especially when plugged into Mathematica.

Anyway, my final project for the randomized algorithms course is due in a few weeks, so once I complete it, I will post the assignment and the mathematica plugin on my website. So far, it seems like it may be a helpful overview of the research into exponential random graph models (ERGM) for those interested in algorithms.