This book gives students a quick and accessible introduction to many of the most important concepts in the field of algorithmic game theory. It demonstrates these concepts through case studies in online advertising, wireless spectrum auctions, kidney exchange, and network management.
This book gives students a quick and accessible introduction to many of the most important concepts in the field of algorithmic game theory. It demonstrates these concepts through case studies in online advertising, wireless spectrum auctions, kidney exchange, and network management.
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).
Inhaltsangabe
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.
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.
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.
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.
Rezensionen
'There are several features of this book that make it very well suited both for the classroom and for self-study ... if your interest is in understanding how game theory, economics and computer science are cross-pollinating to address challenges of the design of online strategic interactions, this is the book to start with. It is clear, well-organized and makes a compelling introduction to a vibrant field.' David Burke, MAA Reviews
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