CSCI 357
Algorithmic Game Theory Spring 2025
Division III Quantitative/Formal Reasoning

Class Details

This course focuses on topics in game theory and mechanism design from a computational perspective. We will explore questions such as: how to design algorithms that incentivize truthful behavior, that is, where the participants have no incentive to cheat? Should we let drivers selfishly minimize their commute time or let a central algorithm direct traffic? Does Arrow’s impossibility result mean that all voting protocols are doomed? The overarching goal of these questions is to understand and analyze selfish behavior and whether it can or should influence system design. Students will learn how to model and reason about incentives in computational systems both theoretically and empirically. Topics include types of equilibria, efficiency of equilibria, auction design and mechanism design with money, two-sided markets and mechanism design without money, incentives in computational applications such as P2P systems, and computational social choice.
The Class: Format: lecture
Limit: 24
Expected: 24
Class#: 3052
Grading: no pass/fail option, no fifth course option
Requirements/Evaluation: weekly problem sets and/or programming assignments, two midterm exams, and a final project.
Prerequisites: CSCI 256
Enrollment Preferences: current or expected Computer Science majors
Distributions: Division III Quantitative/Formal Reasoning
QFR Notes: The course will consist problem sets and programming assignments in which quantitative/formal reasoning skills are practiced and evaluated.

Class Grid

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