Approximation Algorithms for Combinatorial Auctions with Complement-Free Bidders

Authors:
Shahar Dobzinski;Noam Nisan;Michael Schapira
Affiliations:
Computer Science Department, Cornell University, Ithaca, New York 14853;The School of Computer Science and Engineering, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel;Department of Computer Science, Yale University, New Haven, Connecticut 06520, and Computer Science Division, University of California at Berkeley, Berkeley, California 94720
Venue:
Mathematics of Operations Research
Year:
2010

Citing 16
Cited 6

A threshold of ln n for approximating set cover

Journal of the ACM (JACM)
The space complexity of approximating the frequency moments

Journal of Computer and System Sciences
Combinatorial auctions with decreasing marginal utilities

Proceedings of the 3rd ACM conference on Electronic Commerce
Truth revelation in approximately efficient combinatorial auctions

Journal of the ACM (JACM)
The Communication Complexity of Approximate Set Packing and Covering

ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Combinatorial Auctions

Combinatorial Auctions
On maximizing welfare when utility functions are subadditive

Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Truthful randomized mechanisms for combinatorial auctions

Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Approximation algorithms for allocation problems: Improving the factor of 1 - 1/e

FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
Limitations of VCG-based mechanisms

Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Algorithmic Game Theory

Algorithmic Game Theory
Optimal approximation for the submodular welfare problem in the value oracle model

STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Tight information-theoretic lower bounds for welfare maximization in combinatorial auctions

Proceedings of the 9th ACM conference on Electronic commerce
Computationally feasible VCG mechanisms

Journal of Artificial Intelligence Research
An algorithm for optimal winner determination in combinatorial auctions

IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Inapproximability results for combinatorial auctions with submodular utility functions

WINE'05 Proceedings of the First international conference on Internet and Network Economics

Mechanisms for complement-free procurement

Proceedings of the 12th ACM conference on Electronic commerce
Sketching valuation functions

Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Welfare maximization and the supermodular degree

Proceedings of the 4th conference on Innovations in Theoretical Computer Science
Algorithmic Solutions for Envy-Free Cake Cutting

Operations Research
Algorithmic Solutions for Envy-Free Cake Cutting

Operations Research
A survey of approximability and inapproximability results for social welfare optimization in multiagent resource allocation

Annals of Mathematics and Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

In a combinatorial auction m heterogenous indivisible items are sold to n bidders. This paper considers settings in which the valuation functions of the bidders are known to be complement free (a.k.a. subadditive). We provide several approximation algorithms for the social-welfare maximization problem in such settings. First, we present a logarithmic upper bound for the case that the access to the valuation functions is via demand queries. For the weaker value queries model we provide a tight O(√m) approximation. Unlike the other algorithms we present, this algorithm is also incentive compatible. Finally, we present two approximation algorithms for the more restricted class of XOS valuations: A simple deterministic algorithm that provides an approximation ratio of two and an optimal e/(e -1) approximation achieved via randomized rounding. We also present optimal lower bounds for both the demand oracles model and the value oracles model.