COMS 4995: Incentives in Computer Science
- Office hours: Wednesdays 3:45-4:45pm, Mudd 410.
- Email: email@example.com.
- Yaonan Jin
- Office hours: Tuesdays 1:30-3:30pm in the TA room, Mudd first floor.
- Email: firstname.lastname@example.org.
- Office hours: Mondays 3-5pm and Tuesdays 11:30am-1:30pn in the TA
room, Mudd first floor.
- Email: email@example.com.
Time/location: 1:10-3:40 PM Wednesdays, in
room 411 of the International Affairs building.
Piazza site: here
Prerequisites: Mathematical maturity at the level of
a 4000-level course such as algorithms (CSOR 4231) or complexity (COMS 4236).
Programming maturity at the level of COMS W3134.
Many 21st-century computer science applications require the design of software or systems that interact with multiple self-interested participants. This course will provide students with the vocabulary and modeling tools to reason about such design problems. Emphasis will be on understanding basic economic and game theoretic concepts that are relevant across many application domains, and on case studies that demonstrate how to apply these concepts to real-world design problems. Topics include auctions (for spectrum and online advertising), equilibrium analysis, cryptocurrencies, network protocols, two-sided markets (online labor markets, dating markets, etc.), crowdsourcing, reputation systems, and social choice. Case studies include Bitcoin and Ethereum, eBay's reputation system, Facebook's advertising mechanism, Mechanical Turk, and Augur's prediction markets.
There is no official textbook for the course. There will be lecture notes for most of the lectures. One general reference is
Twenty Lectures on Algorithmic Game Theory, which is
based on a more advanced graduate course. (The overlap with this course will be
roughly 20-25%. Though if you enjoy this course, you're likely to
also enjoy many of the topics in this book.)
- Lecture 1 (Room assignment/stable matching): Part 1; Part 2
- Lecture 2 (Markets, Everywhere):
and Sections 1 and 2 here.
- Lecture 3 (Competitive equilibra; information asymmetry):
See Section 3 here
for the first half of lecture, and here for the second.
- Lecture 4 (Sponsored search auctions):
Sections 2 and 3 here, and Sections 1 and 2 here.
- Lecture 5 (VCG and revenue maximization):
See Sections 3 and 4 here and Section 1 here
and Section 3 here.
- More to be posted as the course proceeds.
- Exercise Sets (50%):
Exercise sets will be handed out on Wednesdays and will be due one
week later, by noon.
- Exercise Set Policies:
- To be submitted in groups of 1 or 2
(all students of the group receive the same score).
- You can form different pairs for different exercise sets.
- You can discuss exercises with students from other groups
verbally and at a high level only.
Except where otherwise noted, you may refer to your course notes, the
textbooks and research papers listed on the course Web
page only. You cannot refer to textbooks, handouts, or
research papers that are not listed on the course home page. If you
do use any approved sources, make you sure you cite them
appropriately, and make sure that all your words are your own.
- You are strongly encouraged to use LaTex to typeset your write-up.
Here's a LaTeX template that you can use to
type up solutions. Here
and here are good
introductions to LaTeX.
- Honor code: We expect you to abide by the computer science department's
policies and procedures regarding academic honesty.
- Submission instructions:
We are using Gradescope for the homework submissions. Go to
www.gradescope.com to either login or create a new
account. Use the
course code MKRKK6 to register for this class. Only one group member
needs to submit the assignment. When submitting, please remember to
add all group member names onto Gradescope.
- Late Days:
- One late day equals a 24-hour extension.
- Each student has three free late days.
- At most two late days can be applied to a single assignment;
after Friday (following the original due date) no solutions
will be accepted.
- Each late day used after the first two will result in a 25%
- Example: a student had one free late day remaining but his/her
group uses two late days on a Problem Set. If the group's write-up
earns p points, the student receives a final score of .75*p points
for the assignment.
- Final Project (50%):
This will be a team project, with up to 4 people per team.
For details, deadlines, and some example topics, see here.
Exemplary reports from past offerings:
- Week 1: Introduction to incentives (room assignment and stable matching).
- Week 2: Markets: examples, properties, and design decisions.
- Week 3: Asymmetric information, adverse selection, moral hazard.
- Week 4: Auctions, Part 1 (Vickrey and sponsored search auctions).
- Week 5: Auctions, Part 2 (VCG and spectrum auctions).
- Week 6: Scoring rules, peer grading, prediction markets.
- Week 7: Incentives in cryptocurrencies.
- Week 8: Incentives in networks (communication, peer-to-peer, social, etc.).
- Week 9: The price of anarchy. Time-inconsistent planning.
- Week 10: Social choice: voting and fair division.
- Week 11: Incentives and algorithms in kidney exchange.
- Week 12: Student presentations.
- Week 13: Student presentations.
- Week 14: Student presentations.
- Lecture 1 (Wed Jan 22):
The incentives of room assignment.
Pareto optimality and strategyproofness.
College admissions. One-sided
vs. two-sided markets. The National Resident Matching Program
Stable matchings. Properties of the deferred acceptance
(Gale-Shapley) mechanism. Could college admissions go through a
- Lecture 2 (Wed Jan 29):
Markets from (almost) the 21st century. Centralized vs. decentralized markets. Market failures: timing issues, safety issues, thinness, congestion. Signaling to combat congestion. Markets for goods, with prices.
Demand and supply curves. Market-clearing prices for fungible goods.
- Lecture 3 (Wed Feb 5):
Idiosyncratic goods and competitive equilibrium. First Welfare
Theorem. Existence of competitive equilibria in matching markets with
Adverse selection, moral hazard, and reputation systems.
The market for lemons.
Analogs in health insurance, the labor market, and online platforms.
Sybil attacks. Case study: the evolution of eBay's reputation system.
- Lecture 4 (Wed Feb 12):
Auction design basics.
The Vickrey auction and truthfulness.
Sponsored search auctions: the Generalized Second Price (GSP) and Vickrey-Clarke Groves (VCG) auctions. Case studies: Google and Facebook.
- Lecture 5 (Wed Feb 19):
The general VCG mechanism and its
truthfulness. Practical issues with VCG. Case study: advertising at Facebook.
Case study: reserve prices in Yahoo! keyword auctions.
- Lecture 6 (Wed Feb 26):
- Lecture 7 (Wed Mar 4):
- Lecture 8 (Wed Mar 11):
- [Spring break]
- Lecture 9 (Wed Mar 25):
- Lecture 10 (Wed Apr 1):
- Lecture 11 (Wed Apr 8):
- Lecture 12 (Wed Apr 15):
- Lecture 13 (Wed Apr 22):
- Lecture 14 (Wed Apr 29):