This review summarizes a nascent body of theoretical research on design of incentives
when the environment is not fully known to the designer and offers some general lessons …

We study the role that privacy-preserving algorithms, which prevent the leakage of specific
information about participants, can play in the design of mechanisms for strategic agents …

We present a general framework for approximately reducing the mechanism design problem
for multiple agents to single agent subproblems in the context of Bayesian combinatorial …

When attempting to design a truthful mechanism for a computationally hard problem such as
combinatorial auctions, one is faced with the problem that most efficiently computable …

We give a general technique to obtain approximation mechanisms that are truthful in
expectation. We show that for packing domains, any α-approximation algorithm that also …

It was recently shown in [12] that revenue optimization can be computationally efficiently
reduced to welfare optimization in all multi-dimensional Bayesian auction problems with …

Many advertisers (bidders) use Internet systems to buy display advertisements on
publishers' webpages or on traditional media such as radio, TV and newsprint. They seek a …

We consider a combinatorial auction model where preferences of agents over bundles of
objects and payments need not be quasilinear. However, we restrict the preferences of …

Dramatic advances in DNA sequencing technology have made it possible to study microbial
environments by direct sequencing of environmental DNA samples. Yet, due to the huge …

Abstract In “Single-Value domains”, each agent has the same private value for all desired
outcomes. We formalize this notion and give new examples for such domains, including a …