The Price of Stochastic Anarchy

Chung, Christine; Ligett, Katrina; Pruhs, Kirk; Roth, Aaron

doi:10.1007/978-3-540-79309-0_27

Cited by 18 publications

(26 citation statements)

References 25 publications

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“…Our results are most similar to those from Blum et al [5] and differ from other previous work [6,16,7,17,9,2] (as well as Karakostas et al [10] who model oblivious users in congestion games routing their traffic without regard for congestion) in that we make no assumptions about how irrational or malicious agents should behave. In this sense, we are taking the worst case over adversaries who may engage in sophisticated counter-speculation.…”

Section: Related Worksupporting

confidence: 85%

“…Chung et al [7] study the price of stochastic anarchy for the load balancing game on unrelated machines, which may be viewed as a smoothed analysis of the price of anarchy in a setting in which players are imperfect, who with some small probability make mistakes, playing random actions rather than best responses. They show that imperfect play can actually improve social welfare, by showing that the price of stochastic anarchy is bounded by a function of the number of players and machines, whereas the price of anarchy can be unboundedly large.…”

Section: Related Workmentioning

confidence: 99%

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The Price of Malice in Linear Congestion Games

Roth

2008

Lecture Notes in Computer Science

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We study the price of malice in linear congestion games using the technique of no-regret analysis in the presence of Byzantine players. Our assumptions about the behavior both of rational players, and of malicious players are strictly weaker than have been previously used to study the price of malice. Rather than assuming that rational players route their flow according to a Nash equilibrium, we assume only that the play so as to have no regret. Rather than assuming that malicious players myopically seek to maximize the social cost of the game, we study Byzantine players about whom we make no assumptions, who may be seeking to optimize any utility function, and who may engage in an arbitrary degree of counterspeculation. Because our assumptions are strictly weaker than in previous work, the bounds we prove on two measures of the price of malice hold also for the quantities studied by Babaioff et al. [2] and Moscibroda et al. [17] We prove tight bounds both for the special case of parallel link routing games, and for general congestion games.

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Section: Related Worksupporting

confidence: 85%

Section: Related Workmentioning

confidence: 99%

The Price of Malice in Linear Congestion Games

Roth

2008

Lecture Notes in Computer Science

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“…A related, more detailed summary can be found in [3], in which adaptive learning and imitation dynamics are applied to a load balancing game.…”

Section: Adaptive Learning and Imitation Dynamicsmentioning

confidence: 99%

“…Whenever there is an overflow, the algorithm drops only packets that belong to this flow. 3 The Prince algorithm described in [7] works in a similar manner. The algorithm in [10] was aiming to fulfill, among others, the following two objectives.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Stability in Internet Router Congestion Games

Chung

Pyrga

2009

Algorithmic Game Theory

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Abstract. Congestion control at bottleneck routers on the internet is a long standing problem. Many policies have been proposed for effective ways to drop packets from the queues of these routers so that network endpoints will be inclined to share router capacity fairly and minimize the overflow of packets trying to enter the queues. We study just how effective some of these queuing policies are when each network endpoint is a self-interested player with no information about the other players' actions or preferences. By employing the adaptive learning model of evolutionary game theory, we study policies such as Droptail, RED, and the greedy-flow-punishing policy proposed by Gao et al. [10] to find the stochastically stable states: the states of the system that will be reached in the long run.

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“…Chung et al [9] study the price of anarchy of stochastically stable states of noisy imitation dynamics. They show that the price of anarchy of such states is bounded in the case of unrelated machine scheduling.…”

Section: Introductionmentioning

confidence: 99%

The curse of simultaneity

Leme

Syrgkanis

Tardos

2012

Proceedings of the 3rd Innovations in Theoretical Computer Science Conference

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Typical models of strategic interactions in computer science use simultaneous move games. However, in applications simultaneity is often hard or impossible to achieve. In this paper, we study the robustness of the Nash Equilibrium when the assumption of simultaneity is dropped. In particular we propose studying the sequential price of anarchy: the quality of outcomes of sequential versions of games whose simultaneous counterparts are prototypical in algorithmic game theory. We study different classes of games with high price of anarchy, and show that the subgame perfect equilibrium of their sequential version is a much more natural prediction, ruling out unreasonable equilibria, and leading to much better quality solutions.We consider three examples of such games: Cost Sharing Games, Unrelated Machine Scheduling Games and Consensus Games. For Machine Cost Sharing Games, the sequential price of anarchy is at most O(log(n)), an exponential improvement of the O(n) price of anarchy of their simultaneous counterparts. Further, the subgame perfect equilibrium can be computed by a polynomial time greedy algorithm, and is independent of the order the players arrive. For Unrelated Machine Scheduling Games we show that the sequential price of anarchy is bounded as a function of the number of jobs n and machines m (by at most O(m2 n )), while in the simultaneous version the price of anarchy is unbounded even for two players and two machines. For Consensus Games we observe that the optimal outcome for generic weights is the unique equilibrium that arises in the sequential game. We also study the related Cut Games, where we show that the *

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The Price of Stochastic Anarchy

Cited by 18 publications

References 25 publications

The Price of Malice in Linear Congestion Games

The Price of Malice in Linear Congestion Games

Stochastic Stability in Internet Router Congestion Games

The curse of simultaneity

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