Date of Award
Summer 8-15-2022
Degree Name
Doctor of Philosophy (PhD)
Degree Type
Dissertation
Abstract
Networks permeate every aspect of our social and professional life.A networked system with strategic individuals can represent a variety of real-world scenarios with socioeconomic origins. In such a system, the individuals' utilities are interdependent---one individual's decision influences the decisions of others and vice versa. In order to gain insights into the system, the highly complicated interactions necessitate some level of abstraction. To capture the otherwise complex interactions, I use a game theoretic model called Networked Public Goods (NPG) game. I develop a computational framework based on NPGs to understand strategic individuals' behavior in networked systems. The framework consists of three components that represent different but complementary angles to the understanding. The first part is learning, which aims to produce quantitative and interpretable models of individuals' behavior. The second part focuses on analyzing the individuals' equilibrium behavior, providing guidance on what a rational individual would do when facing other individuals' strategic behavior. The individuals' equilibrium behavior may not be socially preferable, motivating the third part to investigate designing their behavior through network modifications.
Language
English (en)
Chair
Yevgeniy Vorobeychik
Committee Members
David Kempe, Roman Garnett, Brendan Juba, Chien-Ju Ho,