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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 the assignment problem of objects to agents with heterogeneous preferences under distributional constraints. Each agent is associated with a publicly known type and has a private ordinal ranking over objects. We are interested in…

Data Structures and Algorithms · Computer Science 2019-05-02 Itai Ashlagi , Amin Saberi , Ali Shameli

We consider the allocation of indivisible objects when agents have preferences over their own allocations, but share the ownership of the resources to be distributed. Examples might include seats in public schools, faculty offices, and time…

Theoretical Economics · Economics 2021-09-07 Mustafa Oğuz Afacan , Inácio Bó

We investigate revenue guarantees for auction mechanisms in a model where a distribution is specified for each bidder, but only some of the distributions are correct. The subset of bidders whose distribution is correctly specified…

Computer Science and Game Theory · Computer Science 2020-07-22 Makis Arsenis , Odysseas Drosis , Robert Kleinberg

We consider the approval-based model of elections, and undertake a computational study of voting rules which select committees whose size is not predetermined. While voting rules that output committees with a predetermined number of winning…

Computer Science and Game Theory · Computer Science 2017-11-20 Piotr Faliszewski , Arkadii Slinko , Nimrod Talmon

Imitation is a key component of human social behavior, and is widely used by both children and adults as a way to navigate uncertain or unfamiliar situations. But in an environment populated by multiple heterogeneous agents pursuing…

Neurons and Cognition · Quantitative Biology 2023-05-15 Max Taylor-Davies , Stephanie Droop , Christopher G. Lucas

We study revenue optimization pricing algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation. We show that, in the case when both the seller and the buyer…

Computer Science and Game Theory · Computer Science 2018-05-08 Arsenii Vanunts , Alexey Drutsa

In many natural settings agents participate in multiple different auctions that are not simultaneous. In such auctions, future opportunities affect strategic considerations of the players. The goal of this paper is to develop a quantitative…

Computer Science and Game Theory · Computer Science 2012-06-22 Vasilis Syrgkanis , Eva Tardos

This paper studies a general class of social choice problems in which agents' payoff functions (or types) are privately observable random variables, and monetary transfers are not available. We consider cardinal social choice functions…

Theoretical Economics · Economics 2024-08-20 Kazuya Kikuchi , Yukio Koriyama

As recommender systems are being designed and deployed for an increasing number of socially-consequential applications, it has become important to consider what properties of fairness these systems exhibit. There has been considerable…

Information Retrieval · Computer Science 2020-09-08 Nasim Sonboli , Robin Burke , Nicholas Mattei , Farzad Eskandanian , Tian Gao

We improve the best known competitive ratio (from 1/4 to 1/2), for the online multi-unit allocation problem, where the objective is to maximize the single-price revenue. Moreover, the competitive ratio of our algorithm tends to 1, as the…

Computer Science and Game Theory · Computer Science 2009-01-13 Sourav Chakraborty , Nikhil Devanur

Intransitive dice $D^{(1)}, \ldots, D^{(\ell)}$ are dice such that $D^{(1)}$ has advantage when played against $D^{(2)}$, dice $D^{(2)}$ has advantage when played against $D^{(3)}$ and so on, up to $D^{(\ell)}$, which has advantage over…

We present a machine learning-powered iterative combinatorial auction (MLCA). The main goal of integrating machine learning (ML) into the auction is to improve preference elicitation, which is a major challenge in large combinatorial…

Computer Science and Game Theory · Computer Science 2021-09-03 Gianluca Brero , Benjamin Lubin , Sven Seuken

A seller with one unit of a good faces N\geq3 buyers and a single competitor who sells one other identical unit in a second-price auction with a reserve price. Buyers who do not get the seller's good will compete in the competitor's…

Theoretical Economics · Economics 2021-10-26 Kenneth Hendricks , Thomas Wiseman

Strategyproofness in network auctions requires that bidders not only report their valuations truthfully, but also do their best to invite neighbours from the social network. In contrast to canonical auctions, where the value-monotone…

Computer Science and Game Theory · Computer Science 2025-07-22 Yuhang Guo , Dong Hao , Bin Li , Mingyu Xiao , Bakh Khoussainov

We study individual rational, Pareto optimal, and incentive compatible mechanisms for auctions with heterogeneous items and budget limits. For multi-dimensional valuations we show that there can be no deterministic mechanism with these…

Computer Science and Game Theory · Computer Science 2012-10-01 Paul Duetting , Monika Henzinger , Martin Starnberger

Good economic mechanisms depend on the preferences of participants in the mechanism. For example, the revenue-optimal auction for selling an item is parameterized by a reserve price, and the appropriate reserve price depends on how much the…

Computer Science and Game Theory · Computer Science 2014-06-10 Shuchi Chawla , Jason Hartline , Denis Nekipelov

We consider spatial voting where candidates are located in the Euclidean $d$-dimensional space, and each voter ranks candidates based on their distance from the voter's ideal point. We explore the case where information about the location…

Computer Science and Game Theory · Computer Science 2024-08-21 Aviram Imber , Jonas Israel , Markus Brill , Hadas Shachnai , Benny Kimelfeld

Abstraction and realization are bilateral processes that are key in deriving intelligence and creativity. In many domains, the two processes are approached through rules: high-level principles that reveal invariances within similar yet…

Machine Learning · Computer Science 2018-03-13 Haizi Yu , Tianxi Li , Lav R. Varshney

Optimal mechanism design enjoys a beautiful and well-developed theory, and also a number of killer applications. Rules of thumb produced by the field influence everything from how governments sell wireless spectrum licenses to how the major…

Computer Science and Game Theory · Computer Science 2014-09-23 Tim Roughgarden