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12
Intrinsic Robustness of the Price of Anarchy
 STOC'09
, 2009
"... The price of anarchy (POA) is a worstcase measure of the inefficiency of selfish behavior, defined as the ratio of the objective function value of a worst Nash equilibrium of a game and that of an optimal outcome. This measure implicitly assumes that players successfully reach some Nash equilibrium ..."
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The price of anarchy (POA) is a worstcase measure of the inefficiency of selfish behavior, defined as the ratio of the objective function value of a worst Nash equilibrium of a game and that of an optimal outcome. This measure implicitly assumes that players successfully reach some Nash equilibrium. This drawback motivates the search for inefficiency bounds that apply more generally to weaker notions of equilibria, such as mixed Nash and correlated equilibria; or to sequences of outcomes generated by natural experimentation strategies, such as successive best responses or simultaneous regretminimization. We prove a general and fundamental connection between the price of anarchy and its seemingly stronger relatives in classes of games with a sum objective. First, we identify a “canonical sufficient condition ” for an upper bound of the POA for pure Nash equilibria, which we call a smoothness argument. Second, we show that every bound derived via a smoothness argument extends automatically, with no quantitative degradation in the bound, to mixed Nash equilibria, correlated equilibria, and the average objective function value of regretminimizing players (or “price of total anarchy”). Smoothness arguments also have automatic implications for the inefficiency of approximate and BayesianNash equilibria and, under mild additional assumptions, for bicriteria bounds and for polynomiallength bestresponse sequences. We also identify classes of games — most notably, congestion games with cost functions restricted to an arbitrary fixed set — that are tight, in the sense that smoothness arguments are guaranteed to produce an optimal worstcase upper bound on the POA, even for the smallest set of interest (pure Nash equilibria). Byproducts of our proof of this result include the first tight bounds on the POA in congestion games with nonpolynomial cost functions, and the first
The Price of Anarchy in Games of Incomplete Information
 EC'12
, 2012
"... We define smooth games of incomplete information. We prove an “extension theorem” for such games: price of anarchy bounds for pure Nash equilibria for all induced fullinformation games extend automatically, without quantitative degradation, to all mixedstrategy BayesNash equilibria with respect t ..."
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We define smooth games of incomplete information. We prove an “extension theorem” for such games: price of anarchy bounds for pure Nash equilibria for all induced fullinformation games extend automatically, without quantitative degradation, to all mixedstrategy BayesNash equilibria with respect to a product prior distribution over players’ preferences. We also note that, for BayesNash equilibria in games with correlated player preferences, there is no general extension theorem for smooth games. We give several applications of our definition and extension theorem. First, we show that many games of incomplete information for which the price of anarchy has been studied are smooth in our sense. Thus our extension theorem unifies much of the known work on the price of anarchy in games of incomplete information. Second, we use our extension theorem to prove new bounds on the price of anarchy of BayesNash equilibria in congestion games with incomplete information.
Algorithmic Mechanisms for Internetbased MasterWorker Computing with Untrusted and Selfish Workers
, 2010
"... We consider Internetbased masterworker computations, where a master processor assigns, across the Internet, a computational task to a set of untrusted worker processors, and collects their responses; examples of such computations are the “@home” projects such as SETI. Prior work dealing with Inte ..."
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Cited by 3 (1 self)
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We consider Internetbased masterworker computations, where a master processor assigns, across the Internet, a computational task to a set of untrusted worker processors, and collects their responses; examples of such computations are the “@home” projects such as SETI. Prior work dealing with Internetbased task computations has either considered only rational, or only malicious and altruistic workers. Altruistic workers always return the correct result of the task, malicious workers always return an incorrect result, and rational workers act based on their selfinterest. However, in a massive computation platform, such as the Internet, it is expected that all three type of workers coexist. Therefore, in this work we study Internetbased masterworker computations in the presence of Malicious, Altruistic, and Rational workers. A stochastic distribution of the workers over the three types is assumed. Considering all the three types of workers renders a combination of gametheoretic and classical distributed computing approaches to the design of mechanisms for reliable Internetbased computing. Indeed, in this work, such an algorithmic mechanism that makes use of realistic incentives to obtain the correct task result with a parametrized probability is designed. Only when necessary, the incentives are used to force the rational players to a certain equilibrium (which forces the workers to be truthful) that overcomes the attempts of the malicious workers to deceive the master. Finally, the mechanism is analyzed in two realistic Internetbased masterworker applications. This work is an example of how game theory can be used as a tool to formalize and solve a practical Distributed Computing problem such as Internet supercomputing.
How Well Can Congestion Pricing Neutralize Denial of Service Attacks?
"... Denial of service protection mechanisms usually require classifying malicious traffic, which can be difficult. Another approach is to price scarce resources. However, while congestion pricing has been suggested as a way to combat DoS attacks, it has not been shown quantitatively how much damage a ma ..."
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Denial of service protection mechanisms usually require classifying malicious traffic, which can be difficult. Another approach is to price scarce resources. However, while congestion pricing has been suggested as a way to combat DoS attacks, it has not been shown quantitatively how much damage a malicious player could cause to the utility of benign participants. In this paper, we quantify the protection that congestion pricing affords against DoS attacks, even for powerful attackers that can control their packets ’ routes. Specifically, we model the limits on the resources available to the attackers in three different ways and, in each case, quantify the maximum amount of damage they can cause as a function of their resource bounds. In addition, we show that congestion pricing is provably superior to fair queueing in attack resilience.
Game Couplings: Learning Dynamics and Applications
"... Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is ..."
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Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel gametheoretic construct, that we call gamecoupling. Game coupling intuitively allows us to stitch together the payoff structures of subgames. In order to study efficiency issues, we extend the price of anarchy approach (a major focus of gametheoretical multiagent systems [22]) to this setting, where we now care about the performance of each individual subsystem as well as the global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ, µ)smoothness framework [19]. In the second part of the paper, we work on understanding conditions that allow for wellstructured couplings. More generally, we examine when do game couplings preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy.
Altruism in Congestion Games
, 2008
"... This paper studies the effects of introducing altruistic agents into atomic congestion games. Altruistic behavior is modeled by a tradeoff between selfish and social objectives. In particular, we assume agents optimize a linear combination of personal delay of a strategy and the resulting increase ..."
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This paper studies the effects of introducing altruistic agents into atomic congestion games. Altruistic behavior is modeled by a tradeoff between selfish and social objectives. In particular, we assume agents optimize a linear combination of personal delay of a strategy and the resulting increase in social cost. Our model can be embedded in the framework of congestion games with playerspecific latency functions. Stable states are the Nash equilibria of these games, and we examine their existence and the convergence of sequential bestresponse dynamics. Previous work shows that for symmetric singleton games with convex delays Nash equilibria are guaranteed to exist. For concave delay functions we observe that there are games without Nash equilibria and provide a polynomial time algorithm to decide existence for symmetric singleton games with arbitrary delay functions. Our algorithm can be extended to compute best and worst Nash equilibria if they exist. For more general congestion games existence becomes NPhard to decide, even for symmetric network games with quadratic delay functions. Perhaps surprisingly, if all delay functions are linear, then there is always a Nash equilibrium in any congestion game with altruists and any betterresponse dynamics converges. In addition to these results for uncoordinated dynamics, we consider a scenario in which a central altruistic institution can motivate agents to act altruistically. We provide constructive and hardness results for finding the minimum number of altruists to stabilize an optimal congestion profile and more general mechanisms to incentivize agents to adopt favorable behavior.
Fear in Mediation: Exploiting the “Windfall of Malice”
"... We consider a problem at the intersection of distributed computing and game theory, namely: Is it possible to achieve the “windfall of malice ” even without the actual presence of malicious players? Our answer to this question is “Yes and No”. Our positive result is that for the virus inoculation ga ..."
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We consider a problem at the intersection of distributed computing and game theory, namely: Is it possible to achieve the “windfall of malice ” even without the actual presence of malicious players? Our answer to this question is “Yes and No”. Our positive result is that for the virus inoculation game, it is possible to achieve the windfall of malice by use of a mediator. Our negative result is that for congestion games that are known to have a windfall of malice, it is not possible to design a mediator that achieves this windfall. In proving these two results, we develop novel techniques for mediator design that we believe will be helpful for creating nontrivial mediators to improve social welfare in a large class of games. 1
1 Game Couplings: Learning Dynamics and Applications
"... Abstract — Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very ..."
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Abstract — Modern engineering systems (such as the Internet) consist of multiple coupled subsystems. Such subsystems are designed with local (possibly conflicting) goals, with little or no knowledge of the implementation details of other subsystems. Despite the ubiquitous nature of such systems very little is formally known about their properties and global dynamics. We investigate such distributed systems by introducing a novel gametheoretic construct, that we call gamecoupling. Game coupling intuitively allows us to stitch together the payoff structures of two or more games into a new game. In order to study efficiency issues, we extend the price of anarchy framework to this setting, where we now care about local and global performance. Such concerns give rise to a new notion of equilibrium, as well as a new learning paradigm. We prove matching welfare guarantees for both, both for individual subsystems as well as for the global system, using a generalization of the (λ, µ)smoothness framework [17]. In the second part of the paper, we establish conditions leading to advantageous couplings that preserve or enhance desirable properties of the original games, such as convergence of best response dynamics and low price of anarchy. I.
Florin Constantin Research Statement Overview
"... My research is situated at the interface of computer science and game theory, an area of economics studying interactions of strategic players. This interdisciplinary domain has flourished since the advent of the Internet, which greatly facilitates repeated such interactions, e.g. sponsored search an ..."
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My research is situated at the interface of computer science and game theory, an area of economics studying interactions of strategic players. This interdisciplinary domain has flourished since the advent of the Internet, which greatly facilitates repeated such interactions, e.g. sponsored search and information routing. Much of my contributions have been in computational mechanism design (CMD), where the emphasis is on designing systems (e.g. allocation and payment rules) that are resilient to manipulations and have good computational properties. For example, in an auction, manipulations are undesirable because they may complicate bidders ’ behavior, decrease seller’s revenue and result in suboptimal allocations. My current research interests are in algorithmic game theory (AGT), where the focus is more on the algorithmic properties of a given system with selfinterested players rather than the design of such a system for a given class of players. In particular, I have been interested in quantifying the robustness of learning dynamics in games when applied beyond their standard framework. In the following, I summarize my past contributions, review my ongoing work and then outline my research plans. I have striven for rigorous analysis, validated empirically, throughout, with both computer science (algorithms) and economics (game theory) perspectives. The research questions that I find appealing are usually challenging theoretically, but motivated by convincing applications. My work in CMD has taken