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Algorithmic Game Theory

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Cover of 'Algorithmic Game Theory'

Table of Contents

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    Book Overview
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    Chapter 1 When the Players Are Not Expectation Maximizers
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    Chapter 2 How Do You Like Your Equilibrium Selection Problems? Hard, or Very Hard?
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    Chapter 3 A Simplex-Like Algorithm for Fisher Markets
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    Chapter 4 Nash Equilibria in Fisher Market
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    Chapter 5 Partition Equilibrium Always Exists in Resource Selection Games
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    Chapter 6 Mixing Time and Stationary Expected Social Welfare of Logit Dynamics
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    Chapter 7 Pareto Efficiency and Approximate Pareto Efficiency in Routing and Load Balancing Games
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    Chapter 8 On Nash-Equilibria of Approximation-Stable Games
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    Chapter 9 Improved Lower Bounds on the Price of Stability of Undirected Network Design Games
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    Chapter 10 Algorithmic Game Theory
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    Chapter 11 On Learning Algorithms for Nash Equilibria
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    Chapter 12 On the Structure of Weakly Acyclic Games
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    Chapter 13 A Direct Reduction from k -Player to 2-Player Approximate Nash Equilibrium
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    Chapter 14 Responsive Lotteries
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    Chapter 15 On the Existence of Optimal Taxes for Network Congestion Games with Heterogeneous Users
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    Chapter 16 Algorithmic Game Theory
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    Chapter 17 A Perfect Price Discrimination Market Model with Production, and a (Rational) Convex Program for It
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    Chapter 18 The Computational Complexity of Trembling Hand Perfection and Other Equilibrium Refinements
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    Chapter 19 Complexity of Safe Strategic Voting
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    Chapter 20 Bottleneck Congestion Games with Logarithmic Price of Anarchy
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    Chapter 21 Single-Parameter Combinatorial Auctions with Partially Public Valuations
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    Chapter 22 On the Efficiency of Markets with Two-Sided Proportional Allocation Mechanisms
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    Chapter 23 Braess’s Paradox for Flows over Time
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    Chapter 24 The Price of Anarchy in Network Creation Games Is (Mostly) Constant
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    Chapter 25 Truthful Fair Division
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    Chapter 26 No Regret Learning in Oligopolies: Cournot vs. Bertrand
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    Chapter 27 On the Complexity of Pareto-optimal Nash and Strong Equilibria
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    Chapter 28 2-Player Nash and Nonsymmetric Bargaining Games: Algorithms and Structural Properties
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    Chapter 29 On the Inefficiency of Equilibria in Linear Bottleneck Congestion Games
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    Chapter 30 Minimal Subsidies in Expense Sharing Games
Attention for Chapter 26: No Regret Learning in Oligopolies: Cournot vs. Bertrand
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Chapter title
No Regret Learning in Oligopolies: Cournot vs. Bertrand
Chapter number 26
Book title
Algorithmic Game Theory
Published in
ADS, October 2010
DOI 10.1007/978-3-642-16170-4_26
Book ISBNs
978-3-64-216169-8, 978-3-64-216170-4
Authors

Uri Nadav, Georgios Piliouras, Nadav, Uri, Piliouras, Georgios

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 8%
France 1 8%
Taiwan 1 8%
Unknown 10 77%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 23%
Student > Ph. D. Student 3 23%
Student > Doctoral Student 2 15%
Student > Master 2 15%
Professor 1 8%
Other 1 8%
Unknown 1 8%
Readers by discipline Count As %
Engineering 3 23%
Economics, Econometrics and Finance 3 23%
Business, Management and Accounting 2 15%
Computer Science 2 15%
Social Sciences 1 8%
Other 1 8%
Unknown 1 8%