Optimized Democracy
COMPSCI 2380
Subject & Catalog Number
Course Information
Description
The course examines the mathematical and algorithmic foundations of democracy, running the gamut from theory to applications. The goal is to provide students with a rigorous perspective on, and a technical toolbox for, the design of better democratic systems. Topics include computational social choice (identifying optimal voting rules), fairness in political redistricting (avoiding gerrymandering) and apportionment (allocating seats on a representative body), sortition (randomly selecting citizens assemblies), liquid democracy (transitively delegating votes), and weighted voting games (analyzing legislative power through cooperative game theory).
Course Notes
This course was previously numbered CS 238.
Class Notes
Course website: https://sites.google.com/view/optdemocracy26
Recommended Prep
Students should have a basic understanding of probability theory and algorithms. Examples of concepts that are useful to know include Markov chains, concentration inequalities, NP-hardness and linear programming. Mathematical maturity (following proof sketches in real time) is expected. Although this is primarily a graduate course, undergraduate students who have previously taken Statistics 110 and CS 1240 (formerly CS 124) are very welcome.
Available for Harvard Cross Registration
