1 / 24

Efficient Combinatorial Auction Design: Single-Parameter Framework

Explore the design of combinatorial auctions in a single-parameter setting, focusing on truthfulness and social welfare. Discuss Myerson’s characterization, conversion methods, and future directions for optimization. Compare non-Bayesian and Bayesian considerations.

lisamcgrath
Download Presentation

Efficient Combinatorial Auction Design: Single-Parameter Framework

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Single Parameter Combinatorial Auctions Lei Wang Georgia Institute of Technology Joint work with Gagan Goel Chinmay Karande Google Georgia Tech

  2. Overview of Combinatorial Auction • Setting • Mechanism • Allocation: • Payment: • Truthfulness • Social welfare

  3. Our Model and motivation • Motivation

  4. Example: TV ad Auction

  5. Our Model • Public function • Private value: • Valuations

  6. Myerson’s Characterization of truthful mechanism • Monotone allocation: • Payment is determined • Example: VCG mechanism • Approximation algorithm might not be monotone

  7. Our result:

  8. Our conversion • Plan: • Choose a range R • Run MIR • Show:

  9. Construction of our range

  10. Range

  11. Properties

  12. Proof

  13. Conclusion • Conversion

  14. Future direction • Randomized mechanism • Randomized maximum in range • Randomized rounding

  15. Truthfulness v.s. Approximability • Huge clash in non-Bayesian setting • On the hardness of being truthful C.Papadimitriou and Y.Singer FOCS’08 • No clash in Bayesian setting • Bayesian algorithmic mechanism design J.Hartline and B.Lucier STOC’10 • Towards Optimal Bayesian Algorithmic Mechanism Design X.Bei and Z. Huang SODA’11 • Is there any clash for single-parameter?

  16. Thank you! 谢谢

More Related