Computationally Manageable Combinational Auctions
Management Science
Competitive auctions and digital goods
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Truthful approximation mechanisms for restricted combinatorial auctions: extended abstract
Eighteenth national conference on Artificial intelligence
Towards a Characterization of Truthful Combinatorial Auctions
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Revenue failures and collusion in combinatorial auctions and exchanges with vcg payments
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
On profit-maximizing envy-free pricing
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Methods for boosting revenue in combinatorial auctions
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Instantiating the contingent bids model of truthful interdependent value auctions
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Reducing mechanism design to algorithm design via machine learning
Journal of Computer and System Sciences
Stepwise randomized combinatorial auctions achieve revenue monotonicity
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
When Analysis Fails: Heuristic Mechanism Design via Self-correcting Procedures
SOFSEM '09 Proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science
A new approach to auctions and resilient mechanism design
Proceedings of the forty-first annual ACM symposium on Theory of computing
Pick-a-bundle: a novel bundling strategy for selling multiple items within online auctions
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Automated online mechanism design and prophet inequalities
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Revenue monotonicity in combinatorial auctions
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Computing optimal bundles for sponsored search
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Algorithms and theory of computation handbook
Comparing multiagent systems research in combinatorial auctions and voting
Annals of Mathematics and Artificial Intelligence
Discovering theorems in game theory: Two-person games with unique pure Nash equilibrium payoffs
Artificial Intelligence
Truthful auctions with optimal profit
WINE'06 Proceedings of the Second international conference on Internet and Network Economics
Approximating optimal combinatorial auctions for complements using restricted welfare maximization
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Mixed-bundling auctions with reserve prices
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Analysis and optimization of multi-dimensional percentile mechanisms
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Designing revenue-maximizing combinatorial auctions (CAs) is a recognized open problem in mechanism design. It is unsolved even for two bidders and two items for sale. Rather than attempting to characterize the optimal auction, we focus on designing approximations (suboptimal auction mechanisms which yield high revenue). Our approximations belong to the family of virtual valuations combinatorial auctions (VVCA). VVCA is a Vickrey-Clarke-Groves (VCG) mechanism run on virtual valuations that are linear transformations of the bidders' real valuations. We pursue two approaches to constructing approximately optimal CAs. The first is to construct a VVCA with worst-case and average-case performance guarantees. We give a logarithmic approximation auction for basic important special cases of the problem: 1) limited supply of items on sale with additive valuations and 2) unlimited supply. The second approach is to search the parameter space of VVCAs in order to obtain high-revenue mechanisms for the general problem. We introduce a series of increasingly sophisticated algorithms that use economic insights to guide the search and thus reduce the computational complexity. Our experiments demonstrate that in many cases these algorithms perform almost as well as the optimal VVCA, yield a substantial increase in revenue over the VCG mechanism and drastically outperform the straightforward algorithms in run-time.