Algorithmic Game Theory / Edition 1

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Overview

In the last few years game theory has had a substantial impact on computer science, especially on Internet- and e-commerce-related issues. More than 40 of the top researchers in this field have written chapters that go from the foundations to the state of the art. Basic chapters on algorithmic methods for equilibria, mechanism design and combinatorial auctions are followed by chapters on incentives and pricing, cost sharing, information markets and cryptography and security. Students, researchers and practitioners alike need to learn more about these fascinating theoretical developments and their widespread practical application.
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Editorial Reviews

From the Publisher
"The subject matter of Algorithmic Game Theory covers many of the hottest area of useful new game theory research, introducing deep new problems, techniques, and perspectives that demand the attention of economists as well as computer scientists. The all-star list of author-contributors makes this book the best place for newcomers to begin their studies."
Paul Milgrom, Shirley and Leonard Ely Professor of Humanities and Sciences and Professor of Economics, Stanford University

"Computer scientists never lose sight of the fact that a solution to an economic or social problem is not really feasible unless it is computationally tractable, and their toolkit has the potential to give new theoretical flesh to venerable economic intuitions such as the invisible hand, or the problematic nature of market socialism. Algorithmic Game Theory is a collection of essays by leading computer scientists and economists surveying the state of the art, and the open problems, in the many branches of this rapidly moving area. It is ideal for graduate students, and for established researchers in either economics or computer science, who wish to learn about the concepts and issues shaping an increasingly important stream of interdisciplinary research."
Professor Andrew McLennan, School of Economics, University of Queensland

"The most exciting current research in game theory and its applications is being done in computer science. Algorithmic Game Theory effectively brings the reader to the frontiers of this research."
Ehud Kalai, James J. O'Connor Distinguished Professor of Decision and Game Sciences, Kellogg School of Management, Northwestern University

"I recommend Algorithmic Game Theory."
Dave Levin, SIGACT News

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Product Details

  • ISBN-13: 9780521872829
  • Publisher: Cambridge University Press
  • Publication date: 9/30/2007
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 776
  • Product dimensions: 6.97 (w) x 9.96 (h) x 1.61 (d)

Meet the Author

Tim Roughgarden is an Assistant Professor in the Department of Computer Science at Stanford University.

Vijay Vazirani got his Bachelor's degree in Computer Science from MIT in 1979 and his PhD from the University of California at Berkeley in 1983. The central theme in his research career has been the design of efficient algorithms. Additionally, he has also worked on complexity theory, cryptography, coding theory and game theory. In 2001 he published what is widely regarded as the definitive book on Approximation Algorithms; this book has been translated into Japanese, Polish and French. He is a Fellow of the ACM.

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Table of Contents

Introduction Noam Nisan, Tim Roughgarden, Éva Tardos and Vijay V. Vazirani; Part I. Computing in Games: 1. Basic solution concepts and computational issues Éva Tardos and Vijay V. Vazirani; 2. Algorithms for equilibria Christos Papadimitriou; 3. Equilibrium computation for games in strategic and extensive form Bernhard von Stengel; 4. Learning, regret minimization and correlated equilibria Avrim Blum and Yishay Mansour; 5. Graphical games Michael J. Kearns; 6. Cryptography and game theory Yevgeniy Dodis and Tal Rabin; 7. Combinatorial algorithms for market equilibria Vijay V. Vazirani; 8. Computation of market equilibria by convex programming Bruno Codenotti and Kasturi Varadarajan; Part II. Algorithmic Mechanism Design: 9. Introduction to mechanism design (for computer scientists) Noam Nisan; 10. Mechanism design without money James Schummer and Rakesh V. Vohra; 11. Combinatorial auctions Noam Nisan and Liad Blumrosen; 12. Computationally efficient approximation mechanisms Ron Lavi; 13. Profit maximization in mechanism design Jason Hartline and Anna Karlin; 14. Distributed algorithmic mechanism design Joan Feigenbaum, Michael Schapira and Scott Shenker; 15. Cost sharing Kamal Jain and Mohammad Mahdian; 16. On-line mechanisms David C. Parkes; Part III. Quantifying the Inefficiency of Equilibria: 17. Introduction to the inefficiency of equilibria Tim Roughgarden and Éva Tardos; 18. Routing games Tim Roughgarden; 19. Inefficiency of equilibria in network formation games Éva Tardos and Tom Wexler; 20. Selfish load-balancing Berthold Vöcking; 21. Efficiency loss and the design of scalable resource allocation mechanisms Ramesh Johari; Part IV. Additional Topics: 22. Incentives and pricing in communication networks Asuman Ozdaglar and R. Srikant; 23. Incentives in peer-to-peer systems John Chuang, Michal Feldman and Moshe Babaioff; 24. Cascading behavior in networks: algorithmic and economic issues Jon Kleinberg; 25. Incentives and information security Ross Anderson, Tyler Moore, Shishir Nagaraja and Andy Ozment; 26. Computational aspects of information markets David M. Pennock and Rahul Sami; 27. Manipulation-resistant reputation systems Eric Friedman, Paul Resnick and Rahul Sami; 28. Sponsored search auctions Sebastien Lahaie, David M. Pennock, Amin Saberi and Rakesh V. Vohra; 29. Algorithmic issues in evolutionary game theory Michael Kearns and Siddharth Suri.
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Sort by: Showing 1 Customer Reviews
  • Anonymous

    Posted September 22, 2011

    ideal book for those who want to study interdiscpline majors (Econ and cs)

    This is not a book for those who want to learn game theory. This is the book for those who have some knowledge of game theory and want to do computation of equilibria or are interested in CS-related topics.

    Personally, I'm an economic major student but interested in tech related economic topics. before I read this book, I wrote a theoretical model poping out of my mind, which of course didnt reflect the real world. this book gives me clear ideas what cs scientists are doing, then I can incorporate into my economic models which I think it great and helpful.

    1 out of 1 people found this review helpful.

    Was this review helpful? Yes  No   Report this review
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