Introduction to Algorithmic Game Theory

Modern technology platforms, from online ad auctions to decentralized networks, rely on strategic decision-making where multiple self-interested agents interact. This text-based course introduces you to the core principles of algorithmic game theory, bridging the gap between economics and computer science to help you analyze and design these complex systems. You will transition from understanding basic strategic models to analyzing real-world computational markets and mechanism designs. What you'll learn: - Understand foundational game theory concepts including Nash equilibria and dominant strategies - Analyze the computational complexity of finding equilibria in multi-agent environments - Design truthful mechanisms and auctions that align individual incentives with system goals - Evaluate the price of anarchy to measure efficiency loss in decentralized systems - Apply algorithmic game theory concepts to modern applications like ad auctions and network routing This course begins with essential definitions of games, payoffs, and strategic forms, establishing a solid mathematical baseline. You will then progress through computational complexity, mechanism design, and efficiency analysis, learning how to model strategic behavior in algorithmic environments. Written specifically for computer scientists, mathematicians, and economists, this course requires no previous background in game theory. Start reading today to master the algorithms that power modern digital economies.