Computational Social Choice (MS&E 336)

3 credits · Graduate

An in-depth treatment of algorithmic and game-theoretic issues in social choice. Topics include common voting rules and impossibility results; ordinal vs cardinal voting; market approaches to large scale decision making; voting in complex elections, including multi-winner elections and participatory budgeting; protocols for large scale negotiation and deliberation; fairness in societal decision making;algorithmic approaches to governance of modern distributed systems such as blockchains and community-mediated social networks; opinion dynamics and polarization. Prerequisites: algorithms at the level of 212 or CS 161, probability at the level of 221, and basic game theory, or consent of instructor.