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.

Committee Chair

Yevgeniy Vorobeychik

Committee Members

David Kempe, Roman Garnett, Brendan Juba, Chien-Ju Ho,

Degree

Doctor of Philosophy (PhD)

Author's Department

Computer Science & Engineering

Author's School

McKelvey School of Engineering

Document Type

Dissertation

Date of Award

Summer 8-15-2022

Language

English (en)

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