ORF 387 --- Spring 2022

Networks



Basic info

Course description: This course showcases how networks are widespread in society, technology, and nature, via a mix of theory and applications. It demonstrates the importance of understanding network effects when making decisions in an increasingly connected world. Topics include an introduction to graph theory, game theory, social networks, information networks, strategic interactions on networks, network models, network dynamics, information diffusion, and more.

Prerequisites: ORF 309 (Probability and Stochastic Systems) or permission of instructor.

Instructor: Miklos Z. Racz
Lecture time and location: MW 8:30 am - 10:00 am, 101 Sherrerd Hall
Office hours: M 10:00 am - 12:00 pm, 204 Sherrerd Hall or Zoom

Precepts:
Teaching Assistants (AIs):
Undergraduate Course Assistants (UCAs):


Resources

Required text: Discussion: The course has an Ed Discussion page.
Think of this as a Q&A wiki for the course, use it for questions and discussions. For more details, see Ed.



Grading and course policies

Grading: There will be six homework problem sets throughout the semester (roughly evenly spread in time), as well as a midterm and a take-home final exam. There will also be a project component. Your final score is a combination of your performance in these, with the following breakdown:
Midterm info: Wednesday, March 2

Final info: Take-home final exam, during final exam period (details TBA on Ed)

Project info: Projects can be done individually or in groups of two students.
There will be three milestones throughout the semester:
(a) Project proposal (one page: half page background / setup, half page plans & goals). Due Tuesday, February 22.
(b) Progress report. Due Friday, April 1.
(c) Final report. Due Tuesday, May 3 (Dean's Date).
Further details TBA in class.

Homework and collaboration policy:
Please be considerate of the grader and write solutions neatly. Unreadable solutions will not be graded.
Please follow the instructions on the problem set regarding submitting your homework.
Please write your name, Princeton email, and the names of other students you discussed with on the first page of your HW.
No late homework will be accepted. Your lowest homework score will be dropped.

You should first attempt to solve homework problems on your own.
You are encouraged to discuss any remaining difficulties in study groups of two to four people.
However, you must write up the solutions on your own and you must never read or copy the solutions of other students.
Similarly, you may use books or online resources to help solve homework problems, but you must always credit all such sources in your writeup, and you must never copy material verbatim.

Advice: do the homeworks! The best way to understand the material is to solve many problems. In particular, the homeworks are designed to help you learn the material along the way.

Email policy: For questions about the material, please come to office hours.
For general interest questions, please post to the course Ed Discussion page.
This facilitates quick and efficient communication with the class.
Please use email only for emergencies and administrative or personal matters.
Please include "ORF 387" in the subject line of any email about the course.



Schedule

Classes begin on Monday, January 24.

An approximate schedule for the course (chapter references are to the Easley and Kleinberg book):
In addition, the material in the textbook will be supplemented by illustrative examples and applications, especially from the past decade.

Note: this plan is subject to change depending on how we progress throughout the semester.



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