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Core-selecting combinatorial auctions are popular auction designs that constrain prices to eliminate the incentive for any group of bidders -- with the seller -- to renegotiate for a better deal. They help overcome the low-revenue issues of…

Computer Science and Game Theory · Computer Science 2025-05-21 Siddharth Prasad , Maria-Florina Balcan , Tuomas Sandholm

We consider the problem of designing truthful auctions, when the bidders' valuations have a public and a private component. In particular, we consider combinatorial auctions where the valuation of an agent $i$ for a set $S$ of items can be…

Computer Science and Game Theory · Computer Science 2015-05-19 Gagan Goel , Chinmay Karande , Lei Wang

We initiate the study of the communication complexity of fair division with indivisible goods. We focus on some of the most well-studied fairness notions (envy-freeness, proportionality, and approximations thereof) and valuation classes…

Computer Science and Game Theory · Computer Science 2020-03-25 Benjamin Plaut , Tim Roughgarden

We consider a combinatorial auction setting where buyers have fractionally subadditive (XOS) valuations over the items and the seller's objective is to maximize the social welfare. A prophet inequality in this setting bounds the competitive…

Computer Science and Game Theory · Computer Science 2025-05-23 Shuchi Chawla , Trung Dang , Zhiyi Huang , Yifan Wang

We study anonymous posted price mechanisms for combinatorial auctions in a Bayesian framework. In a posted price mechanism, item prices are posted, then the consumers approach the seller sequentially in an arbitrary order, each purchasing…

Computer Science and Game Theory · Computer Science 2014-11-19 Michal Feldman , Nick Gravin , Brendan Lucier

We study a class of iterative combinatorial auctions which can be viewed as subgradient descent methods for the problem of pricing bundles to balance supply and demand. We provide concrete convergence rates for auctions in this class,…

Computer Science and Game Theory · Computer Science 2016-06-01 Jacob Abernethy , Sébastien Lahaie , Matus Telgarsky

Computational and economic results suggest that social welfare maximization and combinatorial auction design are much easier when bidders' valuations satisfy the "gross substitutes" condition. The goal of this paper is to evaluate…

Computer Science and Game Theory · Computer Science 2016-08-09 Tim Roughgarden , Inbal Talgam-Cohen , Jan Vondrák

The design of revenue-maximizing combinatorial auctions, i.e. multi-item auctions over bundles of goods, is one of the most fundamental problems in computational economics, unsolved even for two bidders and two items for sale. In the…

Machine Learning · Computer Science 2016-06-15 Maria-Florina Balcan , Tuomas Sandholm , Ellen Vitercik

The existence of incentive-compatible computationally-efficient protocols for combinatorial auctions with decent approximation ratios is the paradigmatic problem in computational mechanism design. It is believed that in many cases good…

Computer Science and Game Theory · Computer Science 2009-05-14 Elchanan Mossel , Christos Papadimitriou , Michael Schapira , Yaron Singer

Traditionally, the Bayesian optimal auction design problem has been considered either when the bidder values are i.i.d., or when each bidder is individually identifiable via her value distribution. The latter is a reasonable approach when…

Computer Science and Game Theory · Computer Science 2023-07-11 Nikhil R. Devanur , Zhiyi Huang , Christos-Alexandros Psomas

We study \emph{combinatorial procurement auctions}, where a buyer with a valuation function $v$ and budget $B$ wishes to buy a set of items. Each item $i$ has a cost $c_i$ and the buyer is interested in a set $S$ that maximizes $v(S)$…

Computer Science and Game Theory · Computer Science 2015-03-19 Ashwinkumar Badanidiyuru , Shahar Dobzinski , Sigal Oren

We study revenue maximization in multi-item multi-bidder auctions under the natural item-independence assumption - a classical problem in Multi-Dimensional Bayesian Mechanism Design. One of the biggest challenges in this area is developing…

Computer Science and Game Theory · Computer Science 2022-04-12 Yang Cai , Argyris Oikonomou , Mingfei Zhao

In this work we are concerned with the design of efficient mechanisms while eliciting limited information from the agents. First, we study the performance of sampling approximations in facility location games. Our key result is to show that…

Computer Science and Game Theory · Computer Science 2022-08-26 Ioannis Anagnostides , Dimitris Fotakis , Panagiotis Patsilinakos

We present a computationally-efficient truthful mechanism for combinatorial auctions with subadditive bidders that achieves an $O((\log\!\log{m})^3)$-approximation to the maximum welfare in expectation using $O(n)$ demand queries; here $m$…

Computer Science and Game Theory · Computer Science 2020-10-06 Sepehr Assadi , Thomas Kesselheim , Sahil Singla

The focus of classic mechanism design has been on truthful direct-revelation mechanisms. In the context of combinatorial auctions the truthful direct-revelation mechanism that maximizes social welfare is the VCG mechanism. For many…

Computer Science and Game Theory · Computer Science 2013-10-14 Paul Duetting , Monika Henzinger , Martin Starnberger

We consider the computational complexity of computing Bayes-Nash equilibria in first-price auctions, where the bidders' values for the item are drawn from a general (possibly correlated) joint distribution. We show that when the values and…

Computer Science and Game Theory · Computer Science 2025-06-06 Aris Filos-Ratsikas , Yiannis Giannakopoulos , Alexandros Hollender , Charalampos Kokkalis

We consider the sample complexity of revenue maximization for multiple bidders in unrestricted multi-dimensional settings. Specifically, we study the standard model of $n$ additive bidders whose values for $m$ heterogeneous items are drawn…

Computer Science and Game Theory · Computer Science 2021-04-13 Yannai A. Gonczarowski , S. Matthew Weinberg

We study a natural combinatorial single-principal multi-agent contract design problem, in which a principal motivates a team of agents to exert effort toward a given task. At the heart of our model is a reward function, which maps the agent…

Computer Science and Game Theory · Computer Science 2026-03-04 Paul Duetting , Tomer Ezra , Michal Feldman , Thomas Kesselheim

We show that every universally truthful randomized mechanism for combinatorial auctions with submodular valuations that provides $m^{\frac 1 2 -\epsilon}$ approximation to the social welfare and uses value queries only must use…

Computer Science and Game Theory · Computer Science 2015-03-17 Shahar Dobzinski

We show that computing the optimal social surplus requires $\Omega(mn)$ bits of communication between the website and the bidders in a sponsored search auction with $n$ slots on the website and with tick size of $2^{-m}$ in the discrete…

Computer Science and Game Theory · Computer Science 2023-05-16 Suat Evren