2022SP_COMP_SCI_396-0_SEC7 Special Topics in Computer Science: Online Markets

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Picasso's Bulls

Synopsis: Online markets are causing significant changes to society. Examples include eBay, airBnB, tinder, Uber, stackexchange, and Amazon. This class gives an introduction to the science of online markets combining topics from game theory and economics with topics from machine learning and algorithms. The two main topics of interest are how individuals in these marketplaces optimize their strategies and how the market designer optimizes the rules of the market place so that, when individuals optimize their strategies, desired market outcomes are achieved.  Lectures will develop intuition for these topics through mathematical analysis.  Student work will be a mix of exercises, quizzes, short projects, and peer reviews.

Prerequisites: CS 212 (Discrete Math) and CS 214 (Data Structures) or CS 336 (Algorithms) or ECON 380-1 (Game Theory).

Instructor: Jason Hartline
Office hours: Wednesday 1-2pm in Mudd 3015
Lectures: TuTh 2:00-3:20pm in Tech LR4.
Discussion: Piazza.

Teaching Assistants: Sheng Long Links to an external site.
Office hours:

  • Monday 2-3pm in Annenberg G31 
  • Tuesday 12-1pm in Mudd 3534

Grading: 40% projects, 20% peer review, 10% exercises, 10% quizzes, 20% final.

Project Policy: Projects are to be done in pairs. Both students must contribute to the solution of all problems. One copy of the assignment should be turned in. Both students will receive the same grade.  Project report guidelines.

Peer Review: Projects will be peer reviewed.  Peer review is part of the dialogue we have about course content, and serves to provide students with quick feedback about their projects.  Peer review logistics.  Peer review rubric and scoring guidelines.

Quiz Policy: Quizzes will be short and intended to assess understanding of facts and concepts in the course.  Questions will primarily be true/false, multiple choice, or numeric answers.  Quizzes are open notes, but to be done individually and without other Internet resources.  See full details on logistics and policies of quizzes.

Lecture Livestreams: Students are expected to attend the in-person classes.  However, to promote a healthy learning atmosphere, all lectures will be livestreamed to Panopto.  Students feeling like their attendance might compromise the health of other students should attend from the livestream.   

Lecture Recordings: Lectures will be recorded and available to students in the class on Panopto.  Per the university policy:  Unauthorized student recording of classroom or other academic activities (including advising sessions or office hours) is prohibited. Unauthorized recording is unethical and may also be a violation of University policy and state law. Students requesting the use of assistive technology as an accommodation should contact AccessibleNU. Unauthorized use of classroom recordings — including distributing or posting them — is also prohibited.  Under the University’s Copyright Policy, faculty own the copyright to instructional materials — including those resources created specifically for the purposes of instruction, such as syllabi, lectures and lecture notes, and presentations.  Students cannot copy, reproduce, display or distribute these materials. Students who engage in unauthorized recording, unauthorized use of a recording or unauthorized distribution of instructional materials will be referred to the appropriate University office for follow-up.

Accessibility and Accommodations: Northwestern University is committed to providing the most accessible learning environment as possible for students with disabilities. Should you anticipate or experience disability-related barriers in the academic setting, please contact AccessibleNU to move forward with the university’s established accommodation process (e: accessiblenu@northwestern.edu; p: 847-467-5530). If you already have established accommodations with AccessibleNU, please let me know as soon as possible, preferably within the first two weeks of the term, so we can work together to implement your disability accommodations. Disability information, including academic accommodations as part of a student’s educational record, is confidential under FERPA regulations.

Tentative Schedule:

Course Summary:

Date Details Due
Thu Mar 31, 2022 Quiz Exercise 1.1: Elevator Plan due by 3:30pm
Quiz Exercise 1.2: Place Your Bids due by 3:30pm
Tue Apr 5, 2022 Quiz Exercise 2.1: Best Response due by 3:30pm
Quiz Exercise 2.2: "Battle of the Sexes" due by 3:30pm
Thu Apr 7, 2022 Quiz Exercise 3.1: Expected Value due by 3:30pm
Quiz Exercise 3.2: Winning Probability due by 3:30pm
Tue Apr 12, 2022 Quiz Exercise 4.1: Online Learning due by 3:30pm
Quiz Exercise 4.2: Follow the Leader due by 3:30pm
Thu Apr 14, 2022 Quiz Exercise 5.1: Expected Payoff due by 3:30pm
Quiz Exercise 5.2: MAB-EW due by 3:30pm
Assignment Project 1: Bid Analysis due by 11:59pm
Mon Apr 18, 2022 Assignment Peer Review 1: Bid Analysis due by 10pm
Tue Apr 19, 2022 Quiz Exercise 6.1: "Battle of the Sexes" Times Two due by 3:30pm
Quiz Exercise 6.2: Optimal Bid due by 3:30pm
Thu Apr 21, 2022 Quiz Exercise 7.1: Discretization due by 3:30pm
Quiz Exercise 7.2: Learning Rate due by 3:30pm
Tue Apr 26, 2022 Quiz Exercise 8.1: Optimal Welfare due by 3:30pm
Quiz Exercise 8.2: Bid Optimization due by 3:30pm
Thu Apr 28, 2022 Quiz Exercise 9.1: Expected Value due by 3:30pm
Quiz Exercise 9.2: Pricing Revenue due by 3:30pm
Assignment Project 2: Online Learning due by 10pm
Sat Apr 30, 2022 Quiz Quiz 1: Weeks 1-3 due by 12:01am
Mon May 2, 2022 Assignment Peer Review 2: Online Learning due by 10pm
Tue May 3, 2022 Quiz Exercise 10.1: Random Pricing due by 3:30pm
Quiz Exercise 10.2: Pricing Lotteries due by 3:30pm
Thu May 5, 2022 Quiz Exercise 11.1: Optimal Pricing due by 3:30pm
Quiz Exercise 11.2: Allocation Rules due by 3:30pm
Tue May 10, 2022 Quiz Exercise 12.1: Expected Payment due by 3:30pm
Quiz Exercise 12.2: Selling Introductions due by 3:30pm
Thu May 12, 2022 Quiz Exercise 13.1: Auction Forensics due by 3:30pm
Quiz Exercise 13.2: Proportional Bids due by 3:30pm
Assignment Project 3: Learning in Games due by 10pm
Quiz Exercise 13.1: Auction Forensics
(1 student)
 due by 11:59pm
Quiz Exercise 13.2: Proportional Bids
(1 student)
 due by 11:59pm
Mon May 16, 2022 Assignment Peer Review 3: Learning in Games due by 10pm
Tue May 17, 2022 Quiz Exercise 14.1: Posted Pricing due by 3:30pm
Quiz Exercise 14.2: Two-day Gamble due by 3:30pm
Thu May 19, 2022 Quiz Exercise 15.1: Random Permutation due by 3:30pm
Quiz Exercise 15.2: Ski Holiday due by 3:30pm
Fri May 20, 2022 Quiz Quiz 2: Weeks 4-6 due by 11:59pm
Thu May 26, 2022 Quiz Exercise DP2.1. Private Grades due by 4:30pm
Quiz Exercise DP2.2: Privacy of Learning due by 4:30pm
Sat May 28, 2022 Assignment Project 4: Online Revenue Maximization due by 10pm
Tue May 31, 2022 Quiz Exercise 16.1: House Allocation due by 3:30pm
Quiz Exercise 16.2: House Pricing due by 3:30pm
Assignment Peer Review 4: Online Revenue Maximization due by 10pm
Thu Jun 2, 2022 Quiz Exercise 17.1: Matching Dual due by 3:30pm
Quiz Exercise 17.2: Externality Pricing due by 3:30pm
Mon Jun 6, 2022 Assignment Final due by 11am
Quiz Final due by 11am
Tue Jun 7, 2022 Assignment Project 5: Inference for Learning Agents (Optional) due by 10pm
Assignment Open PeerPal