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In this paper, we show a tight approximation guarantee for budget-feasible mechanisms with an additive buyer. We propose a new simple randomized mechanism with approximation ratio of $2$, improving the previous best known result of $3$. Our…

Computer Science and Game Theory · Computer Science 2020-07-22 Nick Gravin , Yaonan Jin , Pinyan Lu , Chenhao Zhang

We study a sequential mechanism design problem in which a principal seeks to elicit truthful reports from multiple rational agents while starting with no prior knowledge of agents' beliefs. We introduce Distributionally Robust Adaptive…

Computer Science and Game Theory · Computer Science 2026-04-22 Qiushi Han , David Simchi-Levi , Renfei Tan , Zishuo Zhao

Proportionality is an attractive fairness concept that has been applied to a range of problems including the facility location problem, a classic problem in social choice. In our work, we propose a concept called Strong Proportionality,…

Computer Science and Game Theory · Computer Science 2022-06-15 Haris Aziz , Alexander Lam , Mashbat Suzuki , Toby Walsh

We study the efficiency (in terms of social welfare) of truthful and symmetric mechanisms in one-sided matching problems with {\em dichotomous preferences} and {\em normalized von Neumann-Morgenstern preferences}. We are particularly…

Computer Science and Game Theory · Computer Science 2014-09-18 Marek Adamczyk , Piotr Sankowski , Qiang Zhang

We consider budget feasible mechanisms for procurement auctions with additive valuation functions. For the divisible case, where agents can be allocated fractionally, there exists an optimal mechanism with approximation guarantee $e/(e-1)$…

Computer Science and Game Theory · Computer Science 2022-09-02 Sophie Klumper , Guido Schäfer

It is widely believed that computing payments needed to induce truthful bidding is somehow harder than simply computing the allocation. We show that the opposite is true: creating a randomized truthful mechanism is essentially as easy as a…

Computer Science and Game Theory · Computer Science 2015-11-17 Moshe Babaioff , Robert D. Kleinberg , Aleksandrs Slivkins

How does one allocate a collection of resources to a set of strategic agents in a fair and efficient manner without using money? For in many scenarios it is not feasible to use money to compensate agents for otherwise unsatisfactory…

Computer Science and Game Theory · Computer Science 2012-07-10 Richard Cole , Vasilis Gkatzelis , Gagan Goel

We study truthful mechanisms for matching and related problems in a partial information setting, where the agents' true utilities are hidden, and the algorithm only has access to ordinal preference information. Our model is motivated by the…

Computer Science and Game Theory · Computer Science 2016-10-20 Elliot Anshelevich , Shreyas Sekar

We consider the fundamental mechanism design problem of approximate social welfare maximization under general cardinal preferences on a finite number of alternatives and without money. The well-known range voting scheme can be thought of as…

Computer Science and Game Theory · Computer Science 2014-09-12 Aris Filos-Ratsikas , Peter Bro Miltersen

In participatory budgeting we are given a set of projects---each with a cost, an available budget, and a set of voters who in some form express their preferences over the projects. The goal is to select---based on voter preferences---a…

Multiagent Systems · Computer Science 2020-09-08 Piotr Skowron , Arkadii Slinko , Stanisław Szufa , Nimrod Talmon

We study a truthful facility location problem where one out of $k\geq2$ available facilities must be built at a location chosen from a set of candidate ones in the interval $[0,1]$. This decision aims to accommodate a set of agents with…

Computer Science and Game Theory · Computer Science 2025-05-07 Panagiotis Kanellopoulos , Alexandros A. Voudouris

We study the House Allocation problem (also known as the Assignment problem), i.e., the problem of allocating a set of objects among a set of agents, where each agent has ordinal preferences (possibly involving ties) over a subset of the…

Computer Science and Game Theory · Computer Science 2019-05-10 Piotr Krysta , David Manlove , Baharak Rastegari , Jinshan Zhang

In many settings the power of truthful mechanisms is severely bounded. In this paper we use randomization to overcome this problem. In particular, we construct an FPTAS for multi-unit auctions that is truthful in expectation, whereas there…

Computer Science and Game Theory · Computer Science 2009-08-24 Shahar Dobzinski , Shaddin Dughmi

We present a unified framework for designing deterministic monotone polynomial time approximation schemes (PTAS's) for a wide class of scheduling problems on uniformly related machines. This class includes (among others) minimizing the…

Data Structures and Algorithms · Computer Science 2015-03-20 Leah Epstein , Asaf Levin , Rob van Stee

We study the problem of fairly and truthfully allocating $m$ indivisible items to $n$ agents with additive preferences. Specifically, we consider truthful mechanisms outputting allocations that satisfy EF$^{+u}_{-v}$, where, in an…

Computer Science and Game Theory · Computer Science 2025-12-08 Xiaolin Bu , Biaoshuai Tao

Participatory budgeting is one of the exciting developments in deliberative grassroots democracy. We concentrate on approval elections and propose proportional representation axioms in participatory budgeting, by generalizing relevant…

Computer Science and Game Theory · Computer Science 2017-11-23 Haris Aziz , Barton Lee , Nimrod Talmon

In budget-feasible mechanism design, a buyer wishes to procure a set of items of maximum value from self-interested players. We have a valuation function $v:2^U \to \mathbb{R}_+$, where $U$ is the set of all items, where $v(S)$ specifies…

Computer Science and Game Theory · Computer Science 2026-03-25 Rian Neogi , Kanstantsin Pashkovich , Chaitanya Swamy

Budget-feasible procurement has been a major paradigm in mechanism design since its introduction by Singer (2010). An auctioneer (buyer) with a strict budget constraint is interested in buying goods or services from a group of strategic…

Computer Science and Game Theory · Computer Science 2025-05-30 Georgios Amanatidis , Sophie Klumper , Evangelos Markakis , Guido Schäfer , Artem Tsikiridis

Augmenting the input of algorithms with predictions is an algorithm design paradigm that suggests leveraging a (possibly erroneous) prediction to improve worst-case performance guarantees when the prediction is perfect (consistency), while…

Computer Science and Game Theory · Computer Science 2025-11-20 Georgios Amanatidis , Evangelos Markakis , Christodoulos Santorinaios , Guido Schäfer , Panagiotis Tsamopoulos , Artem Tsikiridis

We present and discuss general techniques for proving inapproximability results for truthful mechanisms. We make use of these techniques to prove lower bounds on the approximability of several non-utilitarian multi-parameter problems. In…

Computer Science and Game Theory · Computer Science 2017-02-16 Ahuva Mu'alem , Michael Schapira