Theses and Dissertations

ORCID

https://orcid.org/0009-0000-0197-6177

Advisor

Chen, Zhiqian

Committee Member

Ballamoole, Snehalatha

Committee Member

Chen, Jingdao

Committee Member

Sivaraman, Vaidyanathan

Date of Degree

5-10-2024

Original embargo terms

Immediate Worldwide Access

Document Type

Graduate Thesis - Open Access

Major

Computer Science

Degree Name

Master of Science (M.S.)

College

James Worth Bagley College of Engineering

Department

Department of Computer Science and Engineering

Abstract

The Braess Paradox is a rare phenomenon that only occurs under specific scenarios. This project aims to study the probability of the Braess Paradox occurring in a Directed Weighted Graph while the number of edges increases. The graphs in the experiment are focused on studying the occurrence of the Braess Paradox in a directed weighted scale-free network while transforming it into a directed weighted complete graph. A simulation model is used to simulate the bots traveling through a network to detect the occurrence of the Braess Paradox, considering the increase of directed weighted edges. A Graph Neural Network (GNN) is later used to train on the data produced by the simulation model.

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