Abstract

Since its inception in the 1980s, the popularity of the Internet has been growing exponentially, resulting in a mass of shared knowledge and fast, cheap communication. Hand-in-hand with these developments, we have seen the birth of a plethora of new systems for facilitating interaction among economic agents from marketplaces like eBay and Google's AdWords to online networking services like MySpace and Match.com. These systems give rise to numerous opportunities for scientific exploration, and such studies are fundamental to the future economic and social success of these systems. Algorithmic game theory is a new paradigm for studying such systems. The goal in this field is to understand the behavior of autonomous selfish agents, and to define rules that encourage them to collectively act in a way that optimizes some system objective such as social welfare or revenue. This course offers a broad overview of hot topics in algorithmic game theory. Each day highlights a different subfield. On the first day, we will discuss basic concepts in game theory including various equilibrium notions, and learn about the complexity of computing equilibria. On the second day, we will consider an important application of algorithmic game theory, namely auction design. In this section of the course, we will discuss generic techniques for revenue and welfare maximization and then study the design of a real-world marketplace, the sponsored-search auctions of Google, Microsoft, and Yahoo! On the third day, we will discuss the emerging field of social networks, with a particular emphasis on predicting how information and technologies diffuse over these networks. Familiarity with basic concepts in probability and computer science is assumed.

You may find the .pdf format of her lectures here: 1st Session (578 KB), 2nd Session (5,972 KB), 3rd Session (6,227 KB)

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