Competitive analysis of incentive compatible on-line auctions
Proceedings of the 2nd ACM conference on Electronic commerce
Truth revelation in approximately efficient combinatorial auctions
Journal of the ACM (JACM)
Iterative combinatorial auctions: achieving economic and computational efficiency
Iterative combinatorial auctions: achieving economic and computational efficiency
Adaptive limited-supply online auctions
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Online auctions with re-usable goods
Proceedings of the 6th ACM conference on Electronic commerce
Combinatorial Auctions
Online Stochastic Combinatorial Optimization
Online Stochastic Combinatorial Optimization
Dynamic Mechanism Design for Online Commerce
Operations Research
Approximating revenue-maximizing combinatorial auctions
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
An ironing-based approach to adaptive online mechanism design in single-valued domains
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Monotone branch-and-bound search for restricted combinatorial auctions
Proceedings of the 13th ACM Conference on Electronic Commerce
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Computational mechanism design (CMD) seeks to understand how to design game forms that induce desirable outcomes in multi-agent systems despite private information, self-interest and limited computational resources. CMD finds application in many settings, in the public sector for wireless spectrum and airport landing rights, to Internet advertising, to expressive sourcing in the supply chain, to allocating computational resources. In meeting the demands for CMD in these rich domains, we often need to bridge from the theory of economic mechanism design to the practice of deployable, computational mechanisms. A compelling example of this need arises in dynamic combinatorial environments, where classic analytic approaches fail and heuristic, computational approaches are required. In this talk I outline the direction of self-correcting mechanisms, which dynamically modify decisions via "output ironing" to ensure truthfulness and provide a fully computational approach to mechanism design. For an application, I suggest heuristic mechanisms for dynamic auctions in which bids arrive over time and supply may also be uncertain.