Twenty Lectures on Algorithmic Game Theory

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516 g
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229x152x20 mm
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Roughgarden, Tim
Tim Roughgarden is an Associate Professor of Computer Science at Stanford University, California. For his research in algorithmic game theory, he has been awarded the ACM Grace Murray Hopper Award, the Presidential Early Career Award for Scientists and Engineers (PECASE), the Kalai Prize in Game Theory and Computer Science, the Social Choice and Welfare Prize, the Mathematical Programming Society's Tucker Prize, and the EATCS-SIGACT Gödel Prize. He wrote the book Selfish Routing and the Price of Anarchy (2005) and coedited the book Algorithmic Game Theory (2007).
This accessible introduction features case studies in online advertising, spectrum auctions, kidney exchange, and network management.
1. Introduction and examples; 2. Mechanism design basics; 3. Myerson's Lemma; 4. Algorithmic mechanism design 34; 5. Revenue-maximizing auctions; 6. Simple near-optimal auctions; 7. Multi-parameter mechanism design; 8. Spectrum auctions; 9. Mechanism design with payment constraints; 10. Kidney exchange and stable matching; 11. Selfish routing and the price of anarchy; 12. Network over-provisioning and atomic selfish routing; 13. Equilibria: definitions, examples, and existence; 14. Robust price-of-anarchy bounds in smooth games; 15. Best-case and strong Nash equilibria; 16. Best-response dynamics; 17. No-regret dynamics; 18. Swap regret and the Minimax theorem; 19. Pure Nash equilibria and PLS-completeness; 20. Mixed Nash equilibria and PPAD-completeness.
Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.

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