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相关论文: Strategyproof Mechanism for Two Heterogeneous Faci…

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We consider the problem of locating a public facility on a line, where a set of $n$ strategic agents report their \emph{locations} and a mechanism determines, either deterministically or randomly, the location of the facility. Game…

计算机科学与博弈论 · 计算机科学 2013-10-29 Michal Feldman , Yoav Wilf

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,…

计算机科学与博弈论 · 计算机科学 2022-06-15 Haris Aziz , Alexander Lam , Mashbat Suzuki , Toby Walsh

We study mechanisms for the facility location problem augmented with predictions of the optimal facility location. We demonstrate that an egalitarian viewpoint which considers both the maximum distance of any agent from the facility and the…

计算机科学与博弈论 · 计算机科学 2025-08-07 Toby Walsh

We take the classic facility location problem and consider a variation, in which each agent's individual cost function is equal to their distance from the facility multiplied by a scaling factor which is determined by the facility…

计算机科学与博弈论 · 计算机科学 2024-12-06 Yu He , Alexander Lam , Minming Li

The facility location with strategic agents is a canonical problem in the literature on mechanism design without money. Recently, Agrawal et. al. considered this problem in the context of machine learning augmented algorithms, where the…

计算机科学与博弈论 · 计算机科学 2024-10-11 Qingyun Chen , Nick Gravin , Sungjin Im

We revisit the problem of designing strategyproof mechanisms for allocating divisible items among two agents who have linear utilities, where payments are disallowed and there is no prior information on the agents' preferences. The…

计算机科学与博弈论 · 计算机科学 2017-04-13 Yun Kuen Cheung

We study the problem of mechanism design for allocating a set of indivisible items among agents with private preferences on items. We are interested in such a mechanism that is strategyproof (where agents' best strategy is to report their…

计算机科学与博弈论 · 计算机科学 2024-08-05 Ankang Sun , Bo Chen

We study the facility location mechanism design problem where $n$ agents report their locations in Euclidean space, and the output is a single facility location. The cost function of each agent is the distance from the returned facility,…

计算机科学与博弈论 · 计算机科学 2026-05-27 Zohar Barak

In the facility location problem, the task is to place one or more facilities so as to minimize the sum of the agent costs for accessing their nearest facility. Heretofore, in the strategic version, agent locations have been assumed to be…

计算机科学与博弈论 · 计算机科学 2025-05-26 Richard Cole , Pranav Jangir

An approximation of strategyproofness in large, two-sided matching markets is highly evident. Through simulations, one can observe that the percentage of agents with useful deviations decreases as the market size grows. Furthermore, there…

多智能体系统 · 计算机科学 2022-11-30 Lars Lien Ankile , Kjartan Krange , Yuto Yagi

In the one-dimensional facility assignment problem, m facilities and n agents are positioned along the real line. Each agent will be assigned to a single facility to receive service. Each facility incurs a building cost, which is shared…

计算机科学与博弈论 · 计算机科学 2024-04-16 Mengfan Ma , Mingyu Xiao , Tian Bai , Xin Cheng

In the strategic facility location problem, a set of agents report their locations in a metric space and the goal is to use these reports to open a new facility, minimizing an aggregate distance measure from the agents to the facility.…

计算机科学与博弈论 · 计算机科学 2024-11-06 Eric Balkanski , Vasilis Gkatzelis , Golnoosh Shahkarami

We consider a two-sided matching problem in which the agents on one side have dichotomous preferences and the other side representing institutions has strict preferences (priorities). It captures several important applications in matching…

计算机科学与博弈论 · 计算机科学 2025-02-17 Haris Aziz , Md. Shahidul Islam , Szilvia Pápai

We study a non-cooperative two-sided facility location game in which facilities and clients behave strategically. This is in contrast to many other facility location games in which clients simply visit their closest facility. Facility…

计算机科学与博弈论 · 计算机科学 2024-06-14 Simon Krogmann , Pascal Lenzner , Alexander Skopalik

We study mechanism design with predictions for the obnoxious facility location problem. We present deterministic strategyproof mechanisms that display tradeoffs between robustness and consistency on segments, squares, circles and trees. All…

计算机科学与博弈论 · 计算机科学 2025-07-17 Gabriel Istrate , Cosmin Bonchis

We address the problem of locating facilities on the $[0,1]$ interval based on reports from strategic agents. The cost of each agent is her distance to the closest facility, and the global objective is to minimize either the maximum cost of…

计算机科学与博弈论 · 计算机科学 2017-01-04 Iddan Golomb , Christos Tzamos

We characterize the class of group-strategyproof mechanisms for the single facility location game in any unconstrained strictly convex space. A mechanism is \emph{group-strategyproof}, if no group of agents can misreport so that all its…

计算机科学与博弈论 · 计算机科学 2020-08-12 Pingzhong Tang , Dingli Yu , Shengyu Zhao

We consider a multi-stage facility reallocation problems on the real line, where a facility is being moved between time stages based on the locations reported by $n$ agents. The aim of the reallocation algorithm is to minimise the social…

计算机科学与博弈论 · 计算机科学 2021-03-25 Bart de Keijzer , Dominik Wojtczak

We consider non-cooperative facility location games where both facilities and clients act strategically and heavily influence each other. This contrasts established game-theoretic facility location models with non-strategic clients that…

计算机科学与博弈论 · 计算机科学 2024-06-17 Simon Krogmann , Pascal Lenzner , Louise Molitor , Alexander Skopalik

In this work we introduce an alternative model for the design and analysis of strategyproof mechanisms that is motivated by the recent surge of work in "learning-augmented algorithms". Aiming to complement the traditional approach in…

计算机科学与博弈论 · 计算机科学 2022-04-05 Priyank Agrawal , Eric Balkanski , Vasilis Gkatzelis , Tingting Ou , Xizhi Tan