LISP @ BU
contact | e: lgreige@bu.edu

Laura Greige

I'm a PhD student in Computer Science at Boston University working under the supervision of Prof. Peter Chin. I hold a Bachelor's degree in Applied Mathematics and Computer Science and a Master's degree in Artificial Intelligence from the University of Pierre and Marie Curie (UPMC Sorbonne University — Paris VI). My primary research interest lies in the area of artificial intelligence, more specifically, in the study of strategic decision making in machines using computational tools such as reinforcement learning and game theory. My CV is available here.

Research Projects

Reinforcement Learning in FlipIt
Current Work
Boston University, Boston, MA
Abstract
Reinforcement learning has shown much success in games such as chess, backgammon and Go. However, in most of these games, agents have full knowledge of the environment at all times. In this project, we describe a deep learning model that successfully optimizes its score using reinforcement learning in a game with incomplete and imperfect information. We apply our model to FlipIt, a two-player game in which both players, the attacker and the defender, compete for ownership of a shared resource and only receive information on the current state (such as the current owner of the resource, or the time since the opponent last moved, etc.) upon making a move. Our model is a deep neural network combined with Q-learning and is trained to maximize the defender’s time of ownership of the resource. Despite the imperfect observations, our model successfully learns an optimal cost-effective counter-strategy and shows the advantages of the use of deep reinforcement learning in game theoretic scenarios. Our results show that it outperforms the Greedy strategy against distributions such as periodic and exponential distributions without any prior knowledge of the opponent’s strategy, and we generalize the model to n-player games.
Information Propagation in Social Networks
Current Work
Boston University, Boston, MA

Internship Experience

AI Scientist Intern
Starting May 2020
Electronic Arts, Redwood City, CA

Teaching Experience

CS111 : Introduction to CS I (Fall 2017, 2018, Spring 2020)
Course description : The first course for computer science majors and anyone seeking a rigorous introduction. Develops computational problem-solving skills by programming in the Python language, and exposes students to a variety of other topics from computer science and its applications.