Opening for a funded Masters student

On AI game playing difficulty

I'm recruiting a funded Masters student to study how AI bots play games. The goal is to systematically understand the kinds of difficulty posed by games to AI algorithms, as well as the robustness of any conclusions. Some example experiments include: looking at how performance scales with parameters such as CPU time and problem size; how sensitive results are to rule variations, choice of algorithm parameters, etc.; and identification of games that maximally differentiate algorithm performance. Two previous papers of mine that give some flavor of this kind of research: [1], [2].

The primary desired skill is ability to run computational simulations, and to collect and analyze data from them. The available funding would pay for four semesters of full-ride Masters tuition, plus 15-20 hours/week of a work-study job during the academic year. The American University Game Lab offers three Masters-level degrees: the MS in Computer Science's Game & Computational Media track, the MA in Game Design, and the MFA in Games and Interactive Media.

The successful applicant would be funded on the National Science Foundation grant Characterizing Algorithm-Relative Difficulty of Agent Benchmarks. This does not have any citizenship/nationality requirements.

Anyone interested should both apply for the desired Masters program through the official application linked above (deadline July 1, though earlier is better), and email me to indicate that they would like to be considered for this scholarship. It's also fine to email me with inquiries before applying.

August 2020 update: This position has now been filled!