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Related papers: Mechanism Design for Maximum Vectors

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An indivisible object may be sold to one of $n$ agents who know their valuations of the object. The seller would like to use a revenue-maximizing mechanism but her knowledge of the valuations' distribution is scarce: she knows only the…

Theoretical Economics · Economics 2020-08-27 Alex Suzdaltsev

We introduce a model of probabilistic verification in mechanism design. The principal elicits a message from the agent and then selects a test to give the agent. The agent's true type determines the probability with which he can pass each…

Theoretical Economics · Economics 2025-01-16 Ian Ball , Deniz Kattwinkel

Herding, where investors imitate others' decisions rather than relying on their own analysis, is a prevalent phenomenon in financial markets. Excessive herding distorts rational decisions, amplifies volatility, and can be exploited by…

Mathematical Finance · Quantitative Finance 2026-04-14 Huisheng Wang , H. Vicky Zhao

Let P be a set of n weighted points, Q be a set of m unweighted points in the plane, and k a non-negative integer. We consider the problem of computing a subset $Q'\subseteq Q$ with size at most k such that the sum of the weights of the…

Data Structures and Algorithms · Computer Science 2024-11-28 Waseem Akram , Sanjeev Saxena

We study a mechanism-design problem in which spiteful agents strive to not only maximize their rewards but also, contingent upon their own payoff levels, seek to lower the opponents' rewards. We characterize all individually rational (IR)…

Computer Science and Game Theory · Computer Science 2025-12-02 Aditya Aradhye , David Lagziel , Eilon Solan

Variational inequalities are a formalism that includes games, minimization, saddle point, and equilibrium problems as special cases. Methods for variational inequalities are therefore universal approaches for many applied tasks, including…

Autonomous agents optimize the reward function we give them. What they don't know is how hard it is for us to design a reward function that actually captures what we want. When designing the reward, we might think of some specific training…

Artificial Intelligence · Computer Science 2020-10-08 Dylan Hadfield-Menell , Smitha Milli , Pieter Abbeel , Stuart Russell , Anca Dragan

Humans have come to rely on machines for reducing excessive information to manageable representations. But this reliance can be abused -- strategic machines might craft representations that manipulate their users. How can a user make good…

Machine Learning · Computer Science 2022-06-20 Vineet Nair , Ganesh Ghalme , Inbal Talgam-Cohen , Nir Rosenfeld

The theory of algorithmic fair allocation is within the center of multi-agent systems and economics in the last decade due to its industrial and social importance. At a high level, the problem is to assign a set of items that are either…

Computer Science and Game Theory · Computer Science 2022-02-18 Haris Aziz , Bo Li , Herve Moulin , Xiaowei Wu

Constrained submodular set function maximization problems often appear in multi-agent decision-making problems with a discrete feasible set. A prominent example is the problem of multi-agent mobile sensor placement over a discrete domain.…

Optimization and Control · Mathematics 2020-12-01 Navid Rezazadeh , Solmaz S. Kia

The article proposes an n-dimensional mathematical model of the visual representation of a linear programming problem. This model makes it possible to use artificial neural networks to solve multidimensional linear optimization problems,…

Optimization and Control · Mathematics 2022-08-18 Nikolay A. Olkhovsky , Leonid B. Sokolinsky

We consider a private variant of the classical allocation problem: given k goods and n agents with individual, private valuation functions over bundles of goods, how can we partition the goods amongst the agents to maximize social welfare?…

Computer Science and Game Theory · Computer Science 2018-03-16 Justin Hsu , Zhiyi Huang , Aaron Roth , Tim Roughgarden , Zhiwei Steven Wu

A monopolistic seller aims to sell an indivisible item to multiple potential buyers. Each buyer's valuation depends on their private type and the item's quality. The seller can observe the quality but it is unknown to buyers. This quality…

Computer Science and Game Theory · Computer Science 2024-11-13 Zhikang Fan , Weiran Shen

We study the trade-offs between strategyproofness and other desiderata, such as efficiency or fairness, that often arise in the design of random ordinal mechanisms. We use approximate strategyproofness to define manipulability, a measure to…

Computer Science and Game Theory · Computer Science 2017-01-11 Timo Mennle , Sven Seuken

We consider the problem of designing auctions which maximize consumer surplus (i.e., the social welfare minus the payments charged to the buyers). In the consumer surplus maximization problem, a seller with a set of goods faces a set of…

Computer Science and Game Theory · Computer Science 2025-03-18 Tomer Ezra , Daniel Schoepflin , Ariel Shaulker

We study mechanism design when agents may have hidden secondary goals which will manifest as non-trivial preferences among outcomes for which their primary utility is the same. We show that in such cases, a mechanism is robust against…

Computer Science and Game Theory · Computer Science 2023-07-25 Renato Paes Leme , Jon Schneider , Hanrui Zhang

We study the design of optimal allocation mechanisms in an environment where agents and goods arrive stochastically. Agents have private types that determine the principal payoff. Either agents or goods can be held in a queue at a flow cost…

Theoretical Economics · Economics 2026-02-05 Zihao Li , Xuandong Chen

We investigate {\em multidimensional covering mechanism-design} problems, wherein there are $m$ items that need to be covered and $n$ agents who provide covering objects, with each agent $i$ having a private cost for the covering objects he…

Computer Science and Game Theory · Computer Science 2013-09-11 Hadi Minooei , Chaitanya Swamy

This paper studies algorithmic decision-making in the presence of strategic individual behaviors, where an ML model is used to make decisions about human agents and the latter can adapt their behavior strategically to improve their future…

Artificial Intelligence · Computer Science 2025-08-22 Tian Xie , Xueru Zhang

Multi-agent systems exhibit complex behaviors that emanate from the interactions of multiple agents in a shared environment. In this work, we are interested in controlling one agent in a multi-agent system and successfully learn to interact…

Machine Learning · Computer Science 2020-01-30 Georgios Papoudakis , Stefano V. Albrecht