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Iterative combinatorial auctions (CAs) are often used in multi-billion dollar domains like spectrum auctions, and speed of convergence is one of the crucial factors behind the choice of a specific design for practical applications. To…

Computer Science and Game Theory · Computer Science 2019-07-12 Gianluca Brero , Sébastien Lahaie , Sven Seuken

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

For Bayesian combinatorial auctions, we present a general framework for approximately reducing the mechanism design problem for multiple buyers to single buyer sub-problems. Our framework can be applied to any setting which roughly…

Computer Science and Game Theory · Computer Science 2012-06-18 Saeed Alaei

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

In a single-parameter mechanism design problem, a provider is looking to sell a service to a group of potential buyers. Each buyer $i$ has a private value $v_i$ for receiving the service and a feasibility constraint restricts which sets of…

Computer Science and Game Theory · Computer Science 2022-02-21 Michal Feldman , Vasilis Gkatzelis , Nick Gravin , Daniel Schoepflin

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

Generating good revenue is one of the most important problems in Bayesian auction design, and many (approximately) optimal dominant-strategy incentive compatible (DSIC) Bayesian mechanisms have been constructed for various auction settings.…

Computer Science and Game Theory · Computer Science 2020-08-07 Jing Chen , Bo Li , Yingkai Li , Pinyan Lu

Two general algorithms based on opportunity costs are given for approximating a revenue-maximizing set of bids an auctioneer should accept, in a combinatorial auction in which each bidder offers a price for some subset of the available…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Karhan Akcoglu , James Aspnes , Bhaskar DasGupta , Ming-Yang Kao

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

Revealed preference techniques are used to test whether a data set is compatible with rational behaviour. They are also incorporated as constraints in mechanism design to encourage truthful behaviour in applications such as combinatorial…

Computer Science and Game Theory · Computer Science 2015-10-29 Shant Boodaghians , Adrian Vetta

The current art in optimal combinatorial auctions is limited to handling the case of single units of multiple items, with each bidder bidding on exactly one bundle (single minded bidders). This paper extends the current art by proposing an…

Computer Science and Game Theory · Computer Science 2010-04-27 Sujit Gujar , Y Narahari

We show that the multiplicative weight update method provides a simple recipe for designing and analyzing optimal Bayesian Incentive Compatible (BIC) auctions, and reduces the time complexity of the problem to pseudo-polynomial in…

Computer Science and Game Theory · Computer Science 2013-04-12 Anand Bhalgat , Sreenivas Gollapudi , Kamesh Munagala

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

There is only one technique for prior-free optimal mechanism design that generalizes beyond the structurally benevolent setting of digital goods. This technique uses random sampling to estimate the distribution of agent values and then…

Computer Science and Game Theory · Computer Science 2011-08-25 Bach Q. Ha , Jason D. Hartline

In this paper we design information elicitation mechanisms for Bayesian auctions. While in Bayesian mechanism design the distributions of the players' private types are often assumed to be common knowledge, information elicitation considers…

Computer Science and Game Theory · Computer Science 2018-06-27 Jing Chen , Bo Li , Yingkai Li

We present an algorithm for computing pure-strategy epsilon-perfect Bayesian equilibria in sequential auctions with continuous action and value spaces. Importantly, our algorithm includes a verification phase that computes an upper bound on…

Computer Science and Game Theory · Computer Science 2025-02-19 Vinzenz Thoma , Vitor Bosshard , Sven Seuken

In this article we consider combinatorial markets with valuations only for singletons and pairs of buy/sell-orders for swapping two items in equal quantity. We provide an algorithm that permits polynomial time market-clearing and -pricing.…

Optimization and Control · Mathematics 2017-10-30 Johannes C. Müller , Sebastian Pokutta , Alexander Martin , Susanne Pape , Andrea Peter , Thomas Winter

We study information design in click-through auctions, in which the bidders/advertisers bid for winning an opportunity to show their ads but only pay for realized clicks. The payment may or may not happen, and its probability is called the…

Computer Science and Game Theory · Computer Science 2024-04-23 Junjie Chen , Minming Li , Haifeng Xu , Song Zuo

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 develop multiattribute auctions that accommodate generalized additive independent (GAI) preferences. We propose an iterative auction mechanism that maintains prices on potentially overlapping GAI clusters of attributes, thus decreases…

Computer Science and Game Theory · Computer Science 2014-01-17 Yagil Engel , Michael P. Wellman
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