|9:00 - 10:00|| Jason Hartline|
Introduction to Bayesian Mechanism Design [slides]
|10:00 - 10:30||Tim Roughgarden |
Simple/Prior-Independent Auctions (Part A) [slides]
|11:00 - 11:30||Tim Roughgarden |
Simple/Prior-Independent Auctions (Part B)
|11:30 - 12:30|| Costis Daskalakis |
Revenue-optimization in multi-item auctions [slides]
|2:30 - 3:30|| Nicole Immorlica |
Black-box reductions from mechanism to algorithm design [slides]
|3:30 - 4:00||Shuchi Chawla |
Non-linear objectives in mechanism design (Part A) [slides]
|4:30 - 5:00||Suchi Chawla |
Non-linear objectives in mechanism design (Part B)
|5:00 - 6:00||Eva Tardos|
Price of Anarchy of Practical Auctions [slides]
Revenue-optimization in multi-item auctions
Speaker: Costis Daskalakis (MIT)
While welfare optimizing mechanism design has been solved in very general settings, even under worst-case assumptions about the agents' preferences, research on revenue optimization has been stagnant. Myerson's seminal work provides a revenue-optimizing single-item auction, but generalizing this auction to more general settings, e.g. multi-item auctions, has been challenging to economists. Algorithmic techniques have enabled breakthroughs on this problem, enabling exactly optimal mechanisms. This lecture will survey work on designing revenue optimal auctions, discuss the relevant combinatorial optimization techniques, and present open problems going forward.
Black-box reductions from mechanism to algorithm design
Speaker: Nicole Immorlica
Computational considerations aside, welfare optimizing mechanism design has been solved, even under worst-case assumptions about the bidders' preferences. It has also been shown that, under worst-case assumptions, not all welfare problems that can be efficiently approximated can also be approximated in a mechanism design setting. On the other hand, Bayesian information about the agents' preferences enables very general, black-box reductions from mechanism to algorithm design. This lecture will survey work on this frontier, outlining challenges in going beyond the fully Bayesian model and the welfare objectives.
Non-linear objectives in mechanism design
Speaker: Shuchi Chawla (University of Wisconsin-Madison)
The mechanism design literature commonly focuses on the welfare and revenue objectives. Less is known for other objectives and typically results are negative, e.g. for minimizing makespan in scheduling jobs to strategic machines. Here, too, the Bayesian perspective has provided ways to circumvent worst-case impossibility results. This lecture will survey work on mechanism design with general objectives.
Price of Anarchy of Practical Auctions
Speaker: Eva Tardos (Cornell)
Auctions used in practice, such as the generalized second price auction of sponsored search, are often not optimal theoretically. Recent work has quantified the loss in objective, e.g. welfare, of using such suboptimal auctions. This lecture will survey this work, outlining challenges in analyzing incomplete information settings.