CS 269I: Incentives in Computer Science


Course Assistants:

Time/location: 9:30-10:50 AM Mon/Wed in room 128 of the Education building.

Piazza site: Here

Prerequisites: Mathematical maturity at the level of undergraduate algorithms (CS161). Programming maturity at the level of 106B/X.

Course Description: 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.

General references: Twenty Lectures on Algorithmic Game Theory, Cambridge University Press, 2016. See also the Amazon page.

The following collection is older and targeted more to researchers than to students, but is still useful for several topics. We will also draw on the following books for some of the lectures.

Lecture notes


Tentative Syllabus (will likely change):

Detailed Lecture Schedule

Previous offering: Fall 2016. (Overlap will be about 75%.)