In competitive sports such as soccer games, we often see players beating opponents with fake moves. When are these moves successful? Can a robot invent such moves on its own? Answering these questions will help better understand the mathematics behind differential games with incomplete information, which include sports games, self-driving, and human-robot interactions in general. Specifically, the student will be working with PhD students on extending a state-of-the-art algorithm for Poker AI to one-on-one scenarios in soccer, i.e., from a dynamic game in discrete time to a differential game in continuous time. The REU position is funded through an NSF National Robotics Initiative project.

Preferred background in mathematics, computer science, or control – Strong math skill is required – REU available for U.S. citizens – Minority preferred – Knowledge in poker and game theory preferred.

Please send resume and transcript to: yiren@asu.edu

https://designinformaticslab.github.io/