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We study Bayesian automated mechanism design in unstructured dynamic environments, where a principal repeatedly interacts with an agent, and takes actions based on the strategic agent's report of the current state of the world. Both the…

Computer Science and Game Theory · Computer Science 2021-05-14 Hanrui Zhang , Vincent Conitzer

Mechanism design for a social utility being the sum of agents' utilities (SoU) is a well-studied problem. There are, however, a number of problems of theoretical and practical interest where a designer may have a different objective than…

Computer Science and Game Theory · Computer Science 2015-09-29 Abhinav Sinha , Achilleas Anastasopoulos

We study a novel class of mechanism design problems in which the outcomes are constrained by the payments. This basic class of mechanism design problems captures many common economic situations, and yet it has not been studied, to our…

Computer Science and Game Theory · Computer Science 2013-12-02 Yaron Singer

In mechanism design theory, a designer would like to implement a desired social choice function which specifies her favorite outcome for each possible profile of agents' types. To do so, the designer constructs a mechanism which describes…

Computer Science and Game Theory · Computer Science 2019-05-02 Haoyang Wu

We investigate the power of randomness in the context of a fundamental Bayesian optimal mechanism design problem--a single seller aims to maximize expected revenue by allocating multiple kinds of resources to "unit-demand" agents with…

Computer Science and Game Theory · Computer Science 2010-02-24 Shuchi Chawla , David Malec , Balasubramanian Sivan

In the mechanism design theory, a designer would like to implement a desired social choice function which specifies her favorite outcome for each possible profile of all agents' types. Traditionally, the designer may be in a dilemma in the…

Computer Science and Game Theory · Computer Science 2019-06-04 Haoyang Wu

We study a classic Bayesian mechanism design setting of monopoly problem for an additive buyer in the presence of budgets. In this setting a monopolist seller with $m$ heterogeneous items faces a single buyer and seeks to maximize her…

Computer Science and Game Theory · Computer Science 2018-10-09 Yu Cheng , Nick Gravin , Kamesh Munagala , Kangning Wang

We study efficiency and budget balance for designing mechanisms in general quasi-linear domains. Green and Laffont (1979) proved that one cannot generically achieve both. We consider strategyproof budget-balanced mechanisms that are…

Computer Science and Game Theory · Computer Science 2017-03-09 Swaprava Nath , Tuomas Sandholm

We study a class of procurement auctions with a budget constraint, where an auctioneer is interested in buying resources or services from a set of agents. Ideally, the auctioneer would like to select a subset of the resources so as to…

Computer Science and Game Theory · Computer Science 2017-10-10 Georgios Amanatidis , Georgios Birmpas , Evangelos Markakis

We consider the problem of budget feasible mechanism design proposed by Singer (2010), but in a Bayesian setting. A principal has a public value for hiring a subset of the agents and a budget, while the agents have private costs for being…

Computer Science and Game Theory · Computer Science 2015-10-22 Eric Balkanski , Jason D. Hartline

The paper designs revenue-maximizing auction mechanisms for agents who aim to maximize their total obtained values rather than the classical quasi-linear utilities. Several models have been proposed to capture the behaviors of such agents…

Computer Science and Game Theory · Computer Science 2023-07-11 Pinyan Lu , Chenyang Xu , Ruilong Zhang

The aggregation of conflicting preferences is a central problem in multiagent systems. The key difficulty is that the agents may report their preferences insincerely. Mechanism design is the art of designing the rules of the game so that…

Computer Science and Game Theory · Computer Science 2014-08-08 Vincent Conitzer , Tuomas Sandholm

The aggregation of conflicting preferences is a central problem in multiagent systems. The key difficulty is that the agents may report their preferences insincerely. Mechanism design is the art of designing the rules of the game so that…

Computer Science and Game Theory · Computer Science 2007-05-23 Vincent Conitzer , Tuomas Sandholm

We develop efficient algorithms to construct utility maximizing mechanisms in the presence of risk averse players (buyers and sellers) in Bayesian settings. We model risk aversion by a concave utility function, and players play…

Computer Science and Game Theory · Computer Science 2012-06-28 Anand Bhalgat , Tanmoy Chakraborty , Sanjeev Khanna

The problem of computing near-optimal contracts in combinatorial settings has recently attracted significant interest in the computer science community. Previous work has provided a rich body of structural and algorithmic insights into this…

Computer Science and Game Theory · Computer Science 2025-06-26 Michal Feldman , Yoav Gal-Tzur , Tomasz Ponitka , Maya Schlesinger

A Bayesian design is given by maximising an expected utility over a design space. The utility is chosen to represent the aim of the experiment and its expectation is taken with respect to all unknowns: responses, parameters and/or models.…

Methodology · Statistics 2019-01-16 Antony M. Overstall , James M. McGree

We initiate the study of mechanism design with outliers, where the designer can discard $z$ agents from the social cost objective. This setting is particularly relevant when some agents exhibit extreme or atypical preferences. As a natural…

Computer Science and Game Theory · Computer Science 2025-09-19 Argyrios Deligkas , Eduard Eiben , Sophie Klumper , Guido Schäfer , Artem Tsikiridis

We consider the classical mathematical economics problem of {\em Bayesian optimal mechanism design} where a principal aims to optimize expected revenue when allocating resources to self-interested agents with preferences drawn from a known…

Computer Science and Game Theory · Computer Science 2010-01-15 Shuchi Chawla , Jason Hartline , David Malec , Balasubramanian Sivan

Bayesian optimization offers a flexible framework to optimize an objective function that is expensive to be evaluated. A Bayesian optimizer iteratively queries the function values on its carefully selected points. Subsequently, it makes a…

Machine Learning · Computer Science 2019-06-25 Yang Li , Yaqiang Yao

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
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