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Algorithmic Game Theory

$48.00 USD

Noam Nisan, Tim Roughgarden, Éva Tardos, Vijay V. Vazirani, Christos Papadimitriou, Bernhard von Stengel, Avrim Blum, Yishay Mansour, Michael J. Kearns, Yevgeniy Dodis, Tal Rabin, Bruno Codenotti, Kasturi Varadarajan, James Schummer, Rakesh V. Vohra, Liad Blumrosen, Ron Lavi, Jason Hartline, Anna Karlin, Joan Feigenbaum, Michal Schapira, Scott Shenker, Kamal Jain, Mohammad Mahdian, David C. Parkes, Tom Wexler, Berthold Vöcking, Ramesh Johari, Asuman Ozdaglar, R. Srikant, John Chuang, Michal Feldman, Moshe Babaioff, Jon Kleinberg, Ross Anderson, Tyler Moore, Shishir Nagaraja, Andy Ozment, David M. Pennock, Rahul Sami, Eric Friedman, Paul Resnick, Sebastien Lahaie, Amin Saberi, Siddharth Suri
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  • 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.

    • First book to cover the whole spectrum of algorithmic game theory
    • Contributions by all the major researchers in the field
    • Applied chapters by researchers and consultants at major firms such as Yahoo, Lehman Brothers, IBM and Microsoft
    Read more

    Reviews & endorsements

    "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

    See more reviews

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    Product details

    • Date Published: December 2007
    • format: Adobe eBook Reader
    • isbn: 9780511352942
    • contains: 36 b/w illus.
    • availability: Adobe Reader ebooks available from eBooks.com
  • 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.

  • Editors

    Noam Nisan, Hebrew University of Jerusalem

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

    Eva Tardos, Cornell University, New York

    Vijay V. Vazirani, Georgia Institute of Technology
    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.

    Contributors

    Noam Nisan, Tim Roughgarden, Éva Tardos, Vijay V. Vazirani, Christos Papadimitriou, Bernhard von Stengel, Avrim Blum, Yishay Mansour, Michael J. Kearns, Yevgeniy Dodis, Tal Rabin, Bruno Codenotti, Kasturi Varadarajan, James Schummer, Rakesh V. Vohra, Liad Blumrosen, Ron Lavi, Jason Hartline, Anna Karlin, Joan Feigenbaum, Michal Schapira, Scott Shenker, Kamal Jain, Mohammad Mahdian, David C. Parkes, Tom Wexler, Berthold Vöcking, Ramesh Johari, Asuman Ozdaglar, R. Srikant, John Chuang, Michal Feldman, Moshe Babaioff, Jon Kleinberg, Ross Anderson, Tyler Moore, Shishir Nagaraja, Andy Ozment, David M. Pennock, Rahul Sami, Eric Friedman, Paul Resnick, Sebastien Lahaie, Amin Saberi, Siddharth Suri

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