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Strategyproof Auctions for Balancing Social Welfare and Fairness
 in Secondary Spectrum Markets,” in Proc. IEEE INFOCOM 2011, April 2011. et al.: DESIGNING TWODIMENSIONAL SPECTRUM AUCTIONS FOR MOBILE SECONDARY USERS 613
"... Abstract—Secondary spectrum access is emerging as a promising approach for mitigating the spectrum scarcity in wireless networks. Coordinated spectrum access for secondary users can be achieved using periodic spectrum auctions. Recent studies on such auction design mostly neglect the repeating natur ..."
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Cited by 32 (10 self)
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Abstract—Secondary spectrum access is emerging as a promising approach for mitigating the spectrum scarcity in wireless networks. Coordinated spectrum access for secondary users can be achieved using periodic spectrum auctions. Recent studies on such auction design mostly neglect the repeating nature of such auctions, and focus on greedily maximizing social welfare. Such auctions can cause subsets of users to experience starvation in the long run, reducing their incentive to continue participating in the auction. It is desirable to increase the diversity of users allocated spectrum in each auction round, so that a tradeoff between social welfare and fairness is maintained. We study truthful mechanisms towards this objective, for both local and global fairness criteria. For local fairness, we introduce randomization into the auction design, such that each user is guaranteed a minimum probability of being assigned spectrum. Computing an optimal, interferencefree spectrum allocation is NPHard; we present an approximate solution, and tailor a payment scheme to guarantee truthful bidding is a dominant strategy for all secondary users. For global fairness, we adopt the classic maxmin fairness criterion. We tailor another auction by applying linear programming techniques for striking the balance between social welfare and maxmin fairness, and for finding feasible channel allocations. In particular, a pair of primal and dual linear programs are utilized to guide the probabilistic selection of feasible allocations towards a desired tradeoff in expectation. I.
Settling the complexity of ArrowDebreu equilibria in markets with additively separable utilities
 IN: PROCEEDINGS OF THE 50TH ANNUAL IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE
, 2009
"... We prove that the problem of computing an ArrowDebreu market equilibrium is PPADcomplete even when all traders use additively separable, piecewiselinear and concave utility functions. In fact, our proof shows that this marketequilibrium problem does not have a fully polynomialtime approximation ..."
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Cited by 31 (5 self)
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We prove that the problem of computing an ArrowDebreu market equilibrium is PPADcomplete even when all traders use additively separable, piecewiselinear and concave utility functions. In fact, our proof shows that this marketequilibrium problem does not have a fully polynomialtime approximation scheme unless every problem in PPAD is solvable in polynomial time.
Strong Mediated Equilibrium
 In Proceedings of AAAI06
, 2006
"... Providing agents with strategies that will be robust against deviations by coalitions is central to the design of multiagent agents. However, such strategies, captured by the notion of strong equilibrium, rarely exist. This paper suggests the use of mediators in order to enrich the set of situati ..."
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Cited by 31 (5 self)
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Providing agents with strategies that will be robust against deviations by coalitions is central to the design of multiagent agents. However, such strategies, captured by the notion of strong equilibrium, rarely exist. This paper suggests the use of mediators in order to enrich the set of situations where we can obtain stability against deviations by coalitions. A mediator is a reliable entity, which can ask the agents for the right to play on their behalf, and is guaranteed to behave in a prespecified way based on messages received from the agents. However, a mediator can not enforce behavior; that is, ∗ An extended abstract of this paper is appearing at the TwentyFirst National Conference on Artificial Intelligence (AAAI06). Almost all proofs are missing from the extended abstract. This Version of the paper contains all of these missing proofs, and provides additional discussions and results. Furthermore, some of the definitions that do appear in the extended abstract have been slightly modified. 1 agents can play in the game directly without the mediator’s help. We prove some general results about mediators, and concentrate on the notion of strong mediated equilibrium; we show that desired behaviors, which are stable against deviations by coalitions, can be obtained using mediators in several class of settings. 1
Game theoretical insights in strategic patrolling: Model and algorithm in normalform
 in Proceedings of the European Conference on Artificial Intelligence (ECAI
"... Abstract. In artificial intelligence literature there is a rising interest in studying strategic interaction situations. In these situations a number of rational agents act strategically, being in competition, and their analysis is carried out by employing game theoretical tools. One of the most ch ..."
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Cited by 31 (7 self)
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Abstract. In artificial intelligence literature there is a rising interest in studying strategic interaction situations. In these situations a number of rational agents act strategically, being in competition, and their analysis is carried out by employing game theoretical tools. One of the most challenging strategic interaction situation is the strategic patrolling: a guard patrols a number of houses in the attempt to catch a rob, which, in its turn, chooses a house to rob in the attempt to be not catched by the guard. Our contribution in this paper is twofold. Firstly, we provide a critique concerning the models presented in literature and we propose a model that is game theoretical satisfactory. Secondly, by exploit the game theoretical analysis to design a solving algorithm more efficient than stateoftheart’s ones. 1
Characterizing truthful multiarmed bandit mechanisms
 In ACMEC
, 2009
"... We consider a multiround auction setting motivated by payperclick auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which is then either clicked or not. An advertiser derives value from clicks; the value of a click is her private information. I ..."
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We consider a multiround auction setting motivated by payperclick auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which is then either clicked or not. An advertiser derives value from clicks; the value of a click is her private information. Initially, neither the auctioneer nor the advertisers have any information about the likelihood of clicks on the advertisements. The auctioneer’s goal is to design a (dominant strategies) truthful mechanism that (approximately) maximizes the social welfare. If the advertisers bid their true private values, our problem is equivalent to the multiarmed bandit problem, and thus can be viewed as a strategic version of the latter. In particular, for both problems the quality of an algorithm can be characterized by regret, the difference in social welfare between the algorithm and the benchmark which always selects the same“best”advertisement. We investigate how the design of multiarmed bandit algorithms is affected by the restriction that the resulting mechanism must be truthful. We find that truthful mechanisms have certain strong structural properties – essentially, they must separate exploration from exploitation – and they incur much higher regret than the optimal multiarmed bandit algorithms. Moreover, we provide a truthful mechanism which (essentially) matches our lower bound on regret.
Price of Anarchy for Greedy Auctions
"... We study mechanisms for utilitarian combinatorial allocation problems, where agents are not assumed to be singleminded. This class of problems includes combinatorial auctions, multiunit auctions, unsplittable flow problems, and others. We focus on the problem of designing mechanisms that approximat ..."
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Cited by 30 (9 self)
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We study mechanisms for utilitarian combinatorial allocation problems, where agents are not assumed to be singleminded. This class of problems includes combinatorial auctions, multiunit auctions, unsplittable flow problems, and others. We focus on the problem of designing mechanisms that approximately optimize social welfare at every BayesNash equilibrium (BNE), which is the standard notion of equilibrium in settings of incomplete information. For a broad class of greedy approximation algorithms, we give a general blackbox reduction to deterministic mechanisms with almost no loss to the approximation ratio at any BNE. We also consider the special case of Nash equilibria in fullinformation games, where we obtain tightened results. This solution concept is closely related to the wellstudied price of anarchy. Furthermore, for a rich subclass of allocation problems, pure Nash equilibria are guaranteed to exist for our mechanisms. For many problems, the approximation factors we obtain at equilibrium improve upon the best known results for deterministic truthful mechanisms. In particular, we exhibit a simple deterministic mechanism for general combinatorial auctions that obtains an O ( √ m) approximation at every BNE. 1
Automated online mechanism design and prophet inequalities
 In AAAI
, 2007
"... Recent work on online auctions for digital goods has explored the role of optimal stopping theory — particularly secretary problems — in the design of approximately optimal online mechanisms. This work generally assumes that the size of the market (number of bidders) is known a priori, but that the ..."
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Cited by 29 (6 self)
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Recent work on online auctions for digital goods has explored the role of optimal stopping theory — particularly secretary problems — in the design of approximately optimal online mechanisms. This work generally assumes that the size of the market (number of bidders) is known a priori, but that the mechanism designer has no knowledge of the distribution of bid values. However, in many realworld applications (such as online ticket sales), the opposite is true: the seller has distributional knowledge of the bid values (e.g., via the history of past transactions in the market), but there is uncertainty about market size. Adopting the perspective of automated mechanism design, introduced by Conitzer and Sandholm, we develop algorithms that compute an optimal, or approximately optimal, online auction mechanism given
Efficiency of ScalarParameterized Mechanisms
"... We consider the problem of allocating a fixed amount of an infinitely divisible resource among multiple competing, fully rational users. We study the efficiency guarantees that are possible when we restrict to mechanisms that satisfy certain scalability constraints motivated by large scale communica ..."
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Cited by 29 (2 self)
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We consider the problem of allocating a fixed amount of an infinitely divisible resource among multiple competing, fully rational users. We study the efficiency guarantees that are possible when we restrict to mechanisms that satisfy certain scalability constraints motivated by large scale communication networks; in particular, we restrict attention to mechanisms where users are restricted to onedimensional strategy spaces. We first study the efficiency guarantees possible when the mechanism is not allowed to price differentiate. We study the worstcase efficiency loss (ratio of the utility associated with a Nash equilibrium to the maximum possible utility), and show that the proportional allocation mechanism of Kelly (1997) minimizes the efficiency loss when users are price anticipating. We then turn our attention to mechanisms where price differentiation is permitted; using an adaptation of the VickreyClarkeGroves class of mechanisms, we construct a class of mechanisms with onedimensional strategy spaces where Nash equilibria are fully efficient. These mechanisms are shown to be fully efficient even in general convex environments, under reasonable assumptions. Our results highlight a fundamental insight in mechanism design: when the pricing flexibility available to the mechanism designer is limited, restricting the strategic flexibility of bidders may actually improve the efficiency guarantee.
MobiCent: a CreditBased Incentive System for Disruption Tolerant Network
"... When Disruption Tolerant Network (DTN) is used in commercial environments, incentive mechanism should be employed to encourage cooperation among selfish mobile users. Key challenges in the design of an incentive scheme for DTN are that disconnections among nodes are the norm rather than exception an ..."
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Cited by 27 (0 self)
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When Disruption Tolerant Network (DTN) is used in commercial environments, incentive mechanism should be employed to encourage cooperation among selfish mobile users. Key challenges in the design of an incentive scheme for DTN are that disconnections among nodes are the norm rather than exception and network topology is time varying. Thus, it is difficult to detect selfish actions that can be launched by mobile users or to predetermine the routing path to be used. In this paper, we propose MobiCent, a creditbased incentive system for DTN. While MobiCent allows the underlying routing protocol to discover the most efficient paths, it is also incentive compatible. Therefore, using MobiCent, rational nodes will not purposely waste transfer opportunity or cheat by creating nonexisting contacts to increase their rewards. MobiCent also provides different payment mechanisms to cater to client that wants to minimize either payment or data delivery delay.
Truthful assignment without money
 In Proceedings of the 11th ACM Conference on Electronic Commerce (EC
, 2010
"... We study the design of truthful mechanisms that do not use payments for the generalized assignment problem (GAP) and its variants. An instance of the GAP consists of a bipartite graph with jobs on one side and machines on the other. Machines have capacities and edges have values and sizes; the goal ..."
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Cited by 26 (0 self)
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We study the design of truthful mechanisms that do not use payments for the generalized assignment problem (GAP) and its variants. An instance of the GAP consists of a bipartite graph with jobs on one side and machines on the other. Machines have capacities and edges have values and sizes; the goal is to construct a welfare maximizing feasible assignment. In our model of private valuations, motivated by impossibility results, the value and sizes on all jobmachine pairs are public information; however, whether an edge exists or not in the bipartite graph is a job’s private information. That is, the selfish agents in our model are the jobs, and their private information is their edge set. We want to design mechanisms that are truthful without money (henceforth strategyproof), and produce assignments whose welfare