Algorithmic Game Theory

doi:10.1017/CBO9780511800481

In recent years game theory has had a substantial impact on computer science, especially on Internet- and e-commerce-related issues. Algorithmic Game Theory, first published in 2007, develops the central ideas and results of this exciting area in a clear and succinct manner. 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 important game theory applications such as incentives and pricing, cost sharing, information markets and cryptography and security. This definitive work will set the tone of research for the next few years and beyond. Students, researchers, and practitioners alike need to learn more about these fascinating theoretical developments and their widespread practical application.

'… a tome to be dipped into by researchers and developers who would want to know more about certain aspects of the field and particular 'state-of-the-art' issues and applications.'

Source: Kybernetes

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Contents

Frontmatter
pp i-iv
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Contents
pp v-xii
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Foreword
pp xiii-xvi
- By Christos H. Papadimitriou
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Preface
pp xvii-xviii
- By Noam Nisan, School of Computer Science and Engineering Hebrew University of Jerusalem, Tim Roughgarden, Department of Computer Science Stanford University, Éva Tardos, Department of Computer Science Cornell University, Vijay V. Vazirani, College of Computing Georgia Institute of Technology
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Contributors
pp xix-xxi
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I - Computing in Games
pp 1-2
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1 - Basic Solution Concepts and Computational Issues
pp 3-28
- By Éva Tardos, Department of Computer Science Cornell University, Vijay V. Vazirani, College of Computing Georgia Institute of Technology
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2 - The Complexity of Finding Nash Equilibria
pp 29-52
- By Christos H. Papadimitriou, Computer Science Division University of California, Berkeley
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3 - Equilibrium Computation for Two-Player Games in Strategic and Extensive Form
pp 53-78
- By Bernhard von Stengel, Department of Mathematics London School of Economics
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4 - Learning, Regret Minimization, and Equilibria
pp 79-102
- By Avrim Blum, Department of Computer Science Carnegie Mellon University, Yishay Mansour, School of Computer Science Tel Aviv University
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5 - Combinatorial Algorithms for Market Equilibria
pp 103-134
- By Vijay V. Vazirani, College of Computing Georgia Institute of Technology
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6 - Computation of Market Equilibria by Convex Programming
pp 135-158
- By Bruno Codenotti, Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Kasturi Varadarajan, Department of Computer Science University of Iowa
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7 - Graphical Games
pp 159-180
- By Michael Kearns, Department of Computer and Information Science University of Pennsylvania
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8 - Cryptography and Game Theory
pp 181-206
- By Yevgeniy Dodis, Department of Computer Science Courant Institute of Mathematical Sciences, New York University, Tal Rabin, T. J. Watson Research Center IBM
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II - Algorithmic Mechanism Design
pp 207-208
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9 - Introduction to Mechanism Design (for Computer Scientists)
pp 209-242
- By Noam Nisan, School of Computer Science and Engineering Hebrew University of Jerusalem
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10 - Mechanism Design without Money
pp 243-266
- By James Schummer, M.E.D.S. Kellogg School of Management Northwestern University, Rakesh V. Vohra, M.E.D.S. Kellogg School of Management Northwestern University
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11 - Combinatorial Auctions
pp 267-300
- By Liad Blumrosen, Microsoft Research Silicon Valley, Noam Nisan, School of Computer Science and Engineering Hebrew University of Jerusalem
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12 - Computationally Efficient Approximation Mechanisms
pp 301-330
- By Ron Lavi, Faculty of Industrial Engineering and Management, The Technion Israel Institute of Technology
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13 - Profit Maximization in Mechanism Design
pp 331-362
- By Jason D. Hartline, Microsoft Research Silicon Valley, Anna R. Karlin, Department of Computer Science and Engineering University of Washington
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14 - Distributed Algorithmic Mechanism Design
pp 363-384
- By Joan Feigenbaum, Computer Science Department Yale University, Michael Schapira, School of Computer Science and Engineering The Hebrew University of Jerusalem, Scott Shenker, EECS Department University of California, Berkeley
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15 - Cost Sharing
pp 385-410
- By Kamal Jain, Microsoft Research Redmond, Mohammad Mahdian, Yahoo! Research Silicon Valley
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16 - Online Mechanisms
pp 411-440
- By David C. Parkes, School of Engineering and Applied Sciences Harvard University
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III - Quantifying the Inefficiency of Equilibria
pp 441-442
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17 - Introduction to the Inefficiency of Equilibria
pp 443-460
- By Tim Roughgarden, Department of Computer Science Stanford University, Éva Tardos, Department of Computer Science Cornell University
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18 - Routing Games
pp 461-486
- By Tim Roughgarden, Department of Computer Science Stanford University
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19 - Network Formation Games and the Potential Function Method
pp 487-516
- By Éva Tardos, Department of Computer Science Cornell University, Tom Wexler, Department of Computer Science Cornell University
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20 - Selfish Load Balancing
pp 517-542
- By Berthold Vöcking, Department of Computer Science RWTH Aachen University
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21 - The Price of Anarchy and the Design of Scalable Resource Allocation Mechanisms
pp 543-568
- By Ramesh Johari, Department of Management Science and Engineering Stanford University
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IV - Additional Topics
pp 569-570
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