Fast Approximation Algorithms for the Knapsack and Sum of Subset Problems
Journal of the ACM (JACM)
Approximation techniques for utilitarian mechanism design
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Typical Properties of Winners and Losers [0.2ex] in Discrete Optimization
SIAM Journal on Computing
Mechanisms for multi-unit auctions
Proceedings of the 8th ACM conference on Electronic commerce
Smoothed Analysis of Multiobjective Optimization
FOCS '09 Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science
On the Power of Randomization in Algorithmic Mechanism Design
FOCS '09 Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science
Black-Box Randomized Reductions in Algorithmic Mechanism Design
FOCS '10 Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science
Multi-unit auctions: beyond roberts
Proceedings of the 12th ACM conference on Electronic commerce
A universally-truthful approximation scheme for multi-unit auctions
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
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Combinatorial auctions are a common abstraction of many complex resource allocation problems: A large number of items (goods, resources) should be assigned to a number of agents (bidders) with different valuations on bundles of items. They are the central representative problem for the field of algorithmic mechanism design. In this field, algorithmic problems are studied in a game theoretic setting in which the input of the algorithm is not publicly known but distributed among a set of selfish agents which would possibly lie about their private information if this would give an advantage to them. A mechanism is called incentive compatible or truthful if it allocates the goods and sets payments for the bidders in such a way that it is a dominant strategy for each bidder to report his/her valuations for different bundles of items in a truthful manner.