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Book ChapterDOI

Nashification and the coordination ratio for a selfish routing game

TLDR
The first result is an O(nm2) time algorithm for Nashification, which can be used in combination with any approximation algorithm for the routing problem to compute a Nash equilibrium of the same quality and yields a PTAS for the computation of a best Nash equilibrium.
Abstract
We study the problem of n users selfishly routing traffic through a network consisting of m parallel related links. Users route their traffic by choosing private probability distributions over the links with the aim of minimizing their private latency. In such an environment Nash equilibria represent stable states of the system: no user can improve its private latency by unilaterally changing its strategy. Nashification is the problem of converting any given non-equilibrium routing into a Nash equilibrium without increasing the social cost. Our first result is an O(nm2) time algorithm for Nashification. This algorithm can be used in combination with any approximation algorithm for the routing problem to compute a Nash equilibrium of the same quality. In particular, this approach yields a PTAS for the computation of a best Nash equilibrium. Furthermore, we prove a lower bound of Ω(2√n) and an upper bound of O(2n) for the number of greedy selfish steps for identical link capacities in the worst case. In the second part of the paper we introduce a new structural parameter which allows us to slightly improve the upper bound on the coordination ratio for pure Nash equilibria in [3]. The new bound holds for the individual coordination ratio and is asymptotically tight. Additionally, we prove that the known upper bound of 1+√4m-3/2 on the coordination ratio for pure Nash equilibria also holds for the individual coordination ratio in case of mixed Nash equilibria, and we determine the range of m for which this bound is tight.

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Citations
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Journal ArticleDOI

Selfish unsplittable flows

TL;DR: It is proved that any weighted network congestion game with linear edge delays admits a pure Nash equilibrium that can be found in pseudo-polynomial time.
Journal ArticleDOI

Convergence time to Nash equilibrium in load balancing

TL;DR: The number of steps required to reach a pure Nash equilibrium in a load balancing scenario where each job behaves selfishly and attempts to migrate to a machine which will minimize its cost is studied.
Book ChapterDOI

Algorithmic Game Theory: Selfish Load Balancing

TL;DR: In this paper, the authors study the price of anarchy for load balancing games in four different variants and investigate the complexity of computing equilibria, and compare them with optimal solutions with respect to the makespan.
Journal ArticleDOI

Distributed Selfish Load Balancing

TL;DR: In this article, a natural protocol for the agents which combines the following desirable features: it can be implemented in a strongly distributed setting, uses no central control, and has good convergence properties.
Proceedings ArticleDOI

Computing Nash equilibria for scheduling on restricted parallel links

TL;DR: A polynomial time algorithm is introduced to compute from any given assignment a pure Nash equilibrium with non-increased makespan, and similar techniques as in the generic Preflow-Push algorithm are used to approximate a schedule with minimum makespan.
References
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Book

A Course in Game Theory

TL;DR: A Course in Game Theory as discussed by the authors presents the main ideas of game theory at a level suitable for graduate students and advanced undergraduates, emphasizing the theory's foundations and interpretations of its basic concepts.
Book ChapterDOI

Non-cooperative games

John F. Nash
TL;DR: In this article, it was shown that the set of equilibrium points of a two-person zero-sum game can be defined as a set of all pairs of opposing "good" strategies.
Book ChapterDOI

Worst-case equilibria

TL;DR: In this paper, the authors propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system and derive upper and lower bounds for this ratio in a model in which several agents share a very simple network.
Journal ArticleDOI

Algorithmic Mechanism Design

TL;DR: This work considers algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own self-interest, and suggests a framework for studying such algorithms.
Proceedings ArticleDOI

Algorithms, games, and the internet

TL;DR: If the Internet is the next great subject for Theoretical Computer Science to model and illuminate mathematically, then Game Theory, and Mathematical Economics more generally, are likely to prove useful tools.