Algorithmic Game Theory: Incentives, Equilibria, and Applications

This excerpt from Tim Roughgarden’s Twenty Lectures on Algorithmic Game Theory introduces the foundational principles of algorithmic game theory, where computer science and economics converge to analyze interactions among self-interested agents. It delves into mechanism design, focusing on creating incentive-compatible systems like second-price auctions that balance social welfare maximization with computational constraints. Core concepts such as dominant strategies, Myerson’s Lemma, and the revelation principle are unpacked, with real-world applications in sponsored search auctions, spectrum auctions, and kidney exchanges.

The text also examines equilibrium concepts—pure and mixed Nash equilibria, correlated equilibria, and coarse correlated equilibria—exploring their computational feasibility and the implications of the price of anarchy. Using case studies and examples, Roughgarden emphasizes the need for thoughtful system design to navigate and leverage strategic behavior effectively.