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139
Strategyproof Sharing of Submodular Costs: budget balance versus efficiency
, 1999
"... A service is produced for a set of agents. The service is binary, each agent either receives service or not, and the total cost of service is a submodular function of the set receiving service. We investigate strategyproof mechanisms that elicit individual willingness to pay, decide who is served ..."
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Cited by 160 (15 self)
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A service is produced for a set of agents. The service is binary, each agent either receives service or not, and the total cost of service is a submodular function of the set receiving service. We investigate strategyproof mechanisms that elicit individual willingness to pay, decide who is served, and then share the cost among them. If such a mechanism is budget balanced (covers cost exactly), it cannot be efficient (serve the surplus maximizing set of users) and viceversa. We characterize the rich family of budget balanced and group strategyproof mechanisms; they correspond to the family of cost sharing formulae where an agent's cost share does not decrease when the set of users expand. The mechanism associated with the Shapley value cost sharing formula is characterized by the property that its worst welfare loss is minimal. When we require efficiency rather than budget balance  the more common route in the literature  we find that there is a single ClarkeGroves mech...
Ascending Auctions with Package Bidding
, 2001
"... A benchmark "package auction" is introduced in which bidders may determine their own packages on which to bid. If all bidders bid straightforwardly, then the outcome is a point in the core of the exchange economy that minimizes the seller's revenue. When goods are substitutes, straightforward biddin ..."
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Cited by 114 (7 self)
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A benchmark "package auction" is introduced in which bidders may determine their own packages on which to bid. If all bidders bid straightforwardly, then the outcome is a point in the core of the exchange economy that minimizes the seller's revenue. When goods are substitutes, straightforward bidding strategies comprise an ex post Nash equilibrium. Compared to the Vickrey auction, the benchmark ascending package auction has cheaper information processing, better handling of budget constraints, and less vulnerability to joint bidding strategies among bidders who would otherwise be losers. Improvements are suggested that speed the auction and limit opportunities for collusion.
Competitive Generalized Auctions
, 2002
"... We describe mechanisms for auctions that are simultaneously truthful (alternately known as strategyproof or incentivecompatible) and guarantee high "net" profit. We make use of appropriate variants of competitive analysis of algorithms in designing and analyzing our mechanisms. Thus, we do not req ..."
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Cited by 89 (19 self)
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We describe mechanisms for auctions that are simultaneously truthful (alternately known as strategyproof or incentivecompatible) and guarantee high "net" profit. We make use of appropriate variants of competitive analysis of algorithms in designing and analyzing our mechanisms. Thus, we do not require any probabilistic assumptions on bids. We present
Competitive Auctions
, 2002
"... We study a class of singleround, sealedbid auctions for items in unlimited supply, such as digital goods. We introduce the notion of competitive auctions. A competitive auction is truthful (i.e., encourages buyers to bid their utility) and yields profit that is roughly within a constant factor of ..."
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Cited by 79 (11 self)
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We study a class of singleround, sealedbid auctions for items in unlimited supply, such as digital goods. We introduce the notion of competitive auctions. A competitive auction is truthful (i.e., encourages buyers to bid their utility) and yields profit that is roughly within a constant factor of the profit of optimal fixed pricing for all inputs. We justify the use of optimal fixed pricing as a benchmark for evaluating competitive auction profit. We show that several randomized auctions are truthful and competitive and that no truthful deterministic auction is competitive. Our results extend to bounded supply markets, for which we also get truthful and competitive auctions.
Computing Shapley values, manipulating value division schemes, and checking core membership in multiissue domains
 IN PROCEEDINGS OF THE NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI
, 2004
"... Coalition formation is a key problem in automated negotiation among selfinterested agents. In order for coalition formation to be successful, a key question that must be answered is how the gains from cooperation are to be distributed. Various solution concepts have been proposed, but the computati ..."
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Cited by 53 (7 self)
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Coalition formation is a key problem in automated negotiation among selfinterested agents. In order for coalition formation to be successful, a key question that must be answered is how the gains from cooperation are to be distributed. Various solution concepts have been proposed, but the computational questions around these solution concepts have received little attention. We study a concise representation of characteristic functions which allows for the agents to be concerned with a number of independent issues that each coalition of agents can address. For example, there may be a set of tasks that the capacityunconstrained agents could undertake, where accomplishing a task generates a certain amount of value (possibly depending on how well the task is accomplished). Given this representation, we show how to quickly compute the Shapley value—a seminal value division scheme that distributes the gains from cooperation fairly in a certain sense. We then show that in (distributed) marginalcontribution based value division schemes, which are known to be vulnerable to manipulation of the order in which the agents are added to the coalition, this manipulation is NPcomplete. Thus, computational complexity serves as a barrier to manipulating the joining order. Finally, we show that given a value division, determining whether some subcoalition has an incentive to break away (in which case we say the division is not in the core) is NPcomplete. So, computational complexity serves to increase the stability of the coalition.
Coalition, cryptography, and stability: Mechanisms for coalition formation in task oriented domains
 In Proceedings of the Twelfth National Conference on Artificial Intelligence, Menlo
, 1994
"... Negotiation among multiple agents remains an important topic of research in Distributed Artificial Intelligence (DAI). Most previous work on this subject, however, has focused on bilateral negotiation, deals that are reached between two agents. There has also been research on nagent agreement which ..."
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Cited by 43 (0 self)
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Negotiation among multiple agents remains an important topic of research in Distributed Artificial Intelligence (DAI). Most previous work on this subject, however, has focused on bilateral negotiation, deals that are reached between two agents. There has also been research on nagent agreement which has considered “consensus mechanisms ” (such as voting), that allow the full group to coordinate itself. These group decisionmaking techniques, however, assume that the entire group will (or has to) coordinate its actions. Subgroups cannot make subagreements that exclude other members of the group. In some domains, however, it may be possible for beneficial agreements to be reached among subgroups of agents, who might be individually motivated to work together to the exclusion of others outside the group. This paper considers this more general case of nagent coalition formation. We present a simple coalition formation mechanism that uses cryptographic techniques for subadditive Task Oriented Domains. The mechanism is efficient, symmetric, and individual rational. When the domain is also concave, the mechanism also satisfies coalition rationality.
Coherent Allocation of Risk Capital
 Journal of Risk
, 1999
"... The allocation problem stems from the diversification e#ect observed in risk measurements of financial portfolios: the sum of the risk measures of many portfolios is typically larger than the risk of all portfolios taken together. The allocation problem is to apportion this "diversification advantag ..."
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Cited by 42 (0 self)
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The allocation problem stems from the diversification e#ect observed in risk measurements of financial portfolios: the sum of the risk measures of many portfolios is typically larger than the risk of all portfolios taken together. The allocation problem is to apportion this "diversification advantage" to the portfolios in a fair manner, to obtain new, firminternal risk evaluations of the portfolios. Our approach is axiomatic, in the sense that we first establish arguably necessary properties of an allocation scheme, and then study schemes that fulfill the properties. Important results from the area of game theory find a direct application, and are used here. Keywords: allocation of risk; coherent risk measure; game theory; Shapley value; AumannShapley prices; RORAC; riskadjusted performance measure. 1 Introduction The underlying theme of this paper is the sharing of costs within the di#erent constituents of a firm. We call this sharing "allocation", as it is assumed that a higher au...
Polyhedral approaches to machine scheduling
, 1996
"... We provide a review and synthesis of polyhedral approaches to machine scheduling problems. The choice of decision variables is the prime determinant of various formulations for such problems. Constraints, such as facet inducing inequalities for corresponding polyhedra, are often needed, in addition ..."
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Cited by 35 (8 self)
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We provide a review and synthesis of polyhedral approaches to machine scheduling problems. The choice of decision variables is the prime determinant of various formulations for such problems. Constraints, such as facet inducing inequalities for corresponding polyhedra, are often needed, in addition to those just required for the validity of the initial formulation, in order to obtain useful lower bounds and structural insights. We review formulations based on time–indexed variables; on linear ordering, start time and completion time variables; on assignment and positional date variables; and on traveling salesman variables. We point out relationship between various models, and provide a number of new results, as well as simplified new proofs of known results. In particular, we emphasize the important role that supermodular polyhedra and greedy algorithms play in many formulations and we analyze the strength of the lower and upper bounds obtained from different formulations and relaxations. We discuss separation algorithms for several classes of inequalities, and their potential applicability in generating cutting planes for the practical solution of such scheduling problems. We also review some recent results on approximation algorithms based on some of these formulations.
What Is Game Theory Trying to Accomplish?
 FRONTIERS OF ECONOMICS, EDITED BY K. ARROW AND S. HONKAPOHJA
, 1985
"... The language of game theory—coalitions, payo¤s, markets, votes— suggests that it is not a branch of abstract mathematics; that it is motivated by and related to the world around us; and that it should be able to ..."
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Cited by 34 (0 self)
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The language of game theory—coalitions, payo¤s, markets, votes— suggests that it is not a branch of abstract mathematics; that it is motivated by and related to the world around us; and that it should be able to
A FASTER SCALING ALGORITHM FOR MINIMIZING SUBMODULAR FUNCTIONS
, 2001
"... Combinatorial strongly polynomial algorithms for minimizing submodular functions have been developed by Iwata,Fleischer,and Fujishige (IFF) and by Schrijver. The IFF algorithm employs a scaling scheme for submodular functions,whereas Schrijver’s algorithm achieves strongly polynomial bound with the ..."
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Cited by 31 (5 self)
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Combinatorial strongly polynomial algorithms for minimizing submodular functions have been developed by Iwata,Fleischer,and Fujishige (IFF) and by Schrijver. The IFF algorithm employs a scaling scheme for submodular functions,whereas Schrijver’s algorithm achieves strongly polynomial bound with the aid of distance labeling. Subsequently,Fleischer and Iwata have described a push/relabel version of Schrijver’s algorithm to improve its time complexity. This paper combines the scaling scheme with the push/relabel framework to yield a faster combinatorial algorithm for submodular function minimization. The resulting algorithm improves over the previously best known bound by essentially a linear factor in the size of the underlying ground set.