Algorithmic Game Theory

Course notes for Stanford’s algorithmic game theory course.

• One-Sided Matching
• Two-Sided Matching
• Top Trading Cycles
• Equilibria in Games
• P2P File-sharing Dilemma
• Market Equilibrium
• Market Failures
• Single-Unit Auctions
• Sponsored Search Auctions
• Prediction Markets and Information Cascades
• Proof-of-Work Blockchains
• Proof of Stake
• Security Markets
• Envy and Fairness
• Index

This is a digital adaptation of unofficial notes from the amazing Eric Gao for Stanford’s CS269I: Incentives in Computer Science, updated to include the course content from Spring 2024.