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Related papers: On Revenue Monotonicity in Combinatorial Auctions

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We study efficiency loss in Bayesian revenue optimal auctions. We quantify this as the worst case ratio of loss in the realized social welfare to the social welfare that can be realized by an efficient auction. Our focus is on auctions with…

Computer Science and Game Theory · Computer Science 2010-09-14 Vineet Abhishek , Bruce Hajek

A line of recent work provides welfare guarantees of simple combinatorial auction formats, such as selling m items via simultaneous second price auctions (SiSPAs) (Christodoulou et al. 2008, Bhawalkar and Roughgarden 2011, Feldman et al.…

Computer Science and Game Theory · Computer Science 2016-04-07 Constantinos Daskalakis , Vasilis Syrgkanis

Simultaneous item auctions are simple procedures for allocating items to bidders with potentially complex preferences over different item sets. In a simultaneous auction, every bidder submits bids on all items simultaneously. The allocation…

Computer Science and Game Theory · Computer Science 2012-09-24 Michal Feldman , Hu Fu , Nick Gravin , Brendan Lucier

We study a type of reverse (procurement) auction problems in the presence of budget constraints. The general algorithmic problem is to purchase a set of resources, which come at a cost, so as not to exceed a given budget and at the same…

Computer Science and Game Theory · Computer Science 2016-10-05 Georgios Amanatidis , Georgios Birmpas , Evangelos Markakis

Auction theory traditionally assumes that bidders' valuation distributions are known to the auctioneer, such as in the celebrated, revenue-optimal Myerson auction. However, this theory does not describe how the auctioneer comes to possess…

Computer Science and Game Theory · Computer Science 2014-07-11 Avrim Blum , Yishay Mansour , Jamie Morgenstern

We compare the expected efficiency of revenue maximizing (or {\em optimal}) mechanisms with that of efficiency maximizing ones. We show that the efficiency of the revenue maximizing mechanism for selling a single item with k + log_{e/(e-1)}…

Computer Science and Game Theory · Computer Science 2009-06-08 Gagan Aggarwal , Gagan Goel , Aranyak Mehta

We study the design of mechanisms in combinatorial auction domains. We focus on settings where the auction is repeated, motivated by auctions for licenses or advertising space. We consider models of agent behaviour in which they either…

Computer Science and Game Theory · Computer Science 2009-10-01 Brendan Lucier

We study the revenue guarantees and approximability of item pricing. Recent work shows that with $n$ heterogeneous items, item-pricing guarantees an $O(\log n)$ approximation to the optimal revenue achievable by any (buy-many) mechanism,…

Computer Science and Game Theory · Computer Science 2021-11-08 Shuchi Chawla , Rojin Rezvan , Yifeng Teng , Christos Tzamos

Maximizing the revenue from selling _more than one_ good (or item) to a single buyer is a notoriously difficult problem, in stark contrast to the one-good case. For two goods, we show that simple "one-dimensional" mechanisms, such as…

Computer Science and Game Theory · Computer Science 2022-09-22 Sergiu Hart , Noam Nisan

Budget feasible mechanism design studies procurement combinatorial auctions where the sellers have private costs to produce items, and the buyer(auctioneer) aims to maximize a social valuation function on subsets of items, under the budget…

Computer Science and Game Theory · Computer Science 2012-11-09 Xiaohui Bei , Ning Chen , Nick Gravin , Pinyan Lu

In budget-feasible mechanism design, there is a set of items $U$, each owned by a distinct seller. The seller of item $e$ incurs a private cost $\overline{c}_e$ for supplying her item. A buyer wishes to procure a set of items from the…

Computer Science and Game Theory · Computer Science 2026-03-04 Rian Neogi , Kanstantsin Pashkovich , Chaitanya Swamy

We study the revenue maximization problem with an imprecisely estimated distribution of a single buyer or several independent and identically distributed buyers given that this estimation is not far away from the true distribution. We use…

Computer Science and Game Theory · Computer Science 2019-03-05 Yingkai Li , Pinyan Lu , Haoran Ye

Classical optimal auction theory assumes that bids reach the seller directly. We study how this picture changes when a revenue-maximizing intermediary controls access to the seller's auction. Motivated by blockchain auctions, online…

Computer Science and Game Theory · Computer Science 2026-05-22 Jingyi Liu , Aviad Rubinstein , Ertem Nusret Tas , S. Matthew Weinberg , Qianfan Zhang

In this paper, we present the first approximation algorithms for the problem of designing revenue optimal Bayesian incentive compatible auctions when there are multiple (heterogeneous) items and when bidders can have arbitrary demand and…

Computer Science and Game Theory · Computer Science 2010-03-30 Sayan Bhattacharya , Gagan Goel , Sreenivas Gollapudi , Kamesh Munagala

We study the asymptotic average-case efficiency of static and anonymous posted prices for $n$ agents and $m(n)$ multiple identical items with $m(n)=o\left(\frac{n}{\log n}\right)$. When valuations are drawn i.i.d from some fixed continuous…

Computer Science and Game Theory · Computer Science 2019-01-09 Urban Larsson , Ron Lavi

Combinatorial auctions are formulated as frustrated lattice gases on sparse random graphs, allowing the determination of the optimal revenue by methods of statistical physics. Transitions between computationally easy and hard regimes are…

Statistical Mechanics · Physics 2009-11-11 Tobias Galla , Michele Leone , Matteo Marsili , Mauro Sellitto , Martin Weigt , Riccardo Zecchina

In mechanism design it is typical to impose incentive compatibility and then derive an optimal mechanism subject to this constraint. By replacing the incentive compatibility requirement with the goal of minimizing expected ex post regret,…

Computer Science and Game Theory · Computer Science 2012-08-07 Paul Duetting , Felix Fischer , Pitchayut Jirapinyo , John K. Lai , Benjamin Lubin , David C. Parkes

We study a setting where agents use no-regret learning algorithms to participate in repeated auctions. \citet{kolumbus2022auctions} showed, rather surprisingly, that when bidders participate in second-price auctions using no-regret bidding…

Computer Science and Game Theory · Computer Science 2024-11-15 Gagan Aggarwal , Anupam Gupta , Andres Perlroth , Grigoris Velegkas

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 consider markets consisting of a set of indivisible items, and buyers that have {\em sharp} multi-unit demand. This means that each buyer $i$ wants a specific number $d_i$ of items; a bundle of size less than $d_i$ has no value, while a…

Computer Science and Game Theory · Computer Science 2015-03-13 Ning Chen , Xiaotie Deng , Paul. W. Goldberg , Jinshan Zhang