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We consider directed graphs over a set of n agents, where an edge (i,j) is taken to mean that agent i supports or trusts agent j. Given such a graph and an integer k\leq n, we wish to select a subset of k agents that maximizes the sum of…

计算机科学与博弈论 · 计算机科学 2009-10-27 Noga Alon , Felix Fischer , Ariel D. Procaccia , Moshe Tennenholtz

We study the problem of selection in the context of Bayesian persuasion. We are given multiple agents with hidden values (or quality scores), to whom resources must be allocated by a welfare-maximizing decision-maker. An intermediary with…

计算机科学与博弈论 · 计算机科学 2025-11-18 Yannan Bai , Kamesh Munagala , Yiheng Shen , Davidson Zhu

In this paper, we study incentive mechanisms for retrieving information from networked agents. Following the model in [Kleinberg and Raghavan 2005], the agents are represented as nodes in an infinite tree, which is generated by a random…

计算机科学与博弈论 · 计算机科学 2013-08-02 Wei Chen , Yajun Wang , Dongxiao Yu , Li Zhang

Recommender systems play an increasingly crucial role in shaping people's opportunities, particularly in online dating platforms. It is essential from the user's perspective to increase the probability of matching with a suitable partner…

信息检索 · 计算机科学 2024-09-04 Yoji Tomita , Tomohiki Yokoyama

In recent years, many applications have deployed incentive mechanisms to promote users' attention and engagement. Most incentive mechanisms determine specific incentive values based on users' attributes (e.g., preferences), while such…

社会与信息网络 · 计算机科学 2022-11-15 Shiqing Wu , Weihua Li , Quan Bai

Impartial selection problems are concerned with the selection of one or more agents from a set based on mutual nominations from within the set. To avoid strategic nominations of the agents, the axiom of impartiality requires that the…

计算机科学与博弈论 · 计算机科学 2024-10-01 Javier Cembrano , Max Klimm , Arturo Merino

We consider a problem of prediction based on opinions elicited from heterogeneous rational agents with private information. Making an accurate prediction with a minimal cost requires a joint design of the incentive mechanism and the…

计算机科学与博弈论 · 计算机科学 2016-02-25 Yuan Luo , Nihar B. Shah , Jianwei Huang , Jean Walrand

We study the statistical design of a fair mechanism that attains equalized odds, where an agent uses some useful data (database) $X$ to solve a task $T$. Since both $X$ and $T$ are correlated with some latent sensitive attribute $S$, the…

信息论 · 计算机科学 2025-12-02 Amirreza Zamani , Ayfer Özgür , Mikael Skoglund

A planner wants to select one agent out of n agents on the basis of a binary characteristic that is commonly known to all agents but is not observed by the planner. Any pair of agents can either be friends or enemies or impartials of each…

理论经济学 · 经济学 2025-11-17 Francis Bloch , Bhaskar Dutta , Marcin Dziubiński

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 a setting in which a principal selects an agent to execute a collection of tasks according to a specified priority sequence. Agents, however, have their own individual priority sequences according to which they wish to execute the…

计算机科学与博弈论 · 计算机科学 2024-10-30 Donya G. Dobakhshari , Lav R. Varshney , Vijay Gupta

This paper investigates causal influences between agents linked by a social graph and interacting over time. In particular, the work examines the dynamics of social learning models and distributed decision-making protocols, and derives…

社会与信息网络 · 计算机科学 2026-05-19 Mert Kayaalp , Ali H. Sayed

We consider a social planner faced with a stream of myopic selfish agents. The goal of the social planner is to maximize the social welfare, however, it is limited to using only information asymmetry (regarding previous outcomes) and cannot…

计算机科学与博弈论 · 计算机科学 2019-05-15 Lee Cohen , Yishay Mansour

We consider the problem of selecting $k$ seed nodes in a network to maximize the minimum probability of activation under an independent cascade beginning at these seeds. The motivation is to promote fairness by ensuring that even the least…

Motivated by kidney exchange, we study the following mechanism-design problem: On a directed graph (of transplant compatibilities among patient-donor pairs), the mechanism must select a simple path (a chain of transplantations) starting at…

计算机科学与博弈论 · 计算机科学 2021-06-23 Avrim Blum , Paul Gölz

We study how to optimally design selection mechanisms, accounting for agents' investment incentives. A principal wishes to allocate a resource of homogeneous quality to a heterogeneous population of agents. The principal commits to a…

理论经济学 · 经济学 2025-11-11 Victor Augias , Eduardo Perez-Richet

We study a family online influence maximization problems where in a sequence of rounds $t=1,\ldots,T$, a decision maker selects one from a large number of agents with the goal of maximizing influence. Upon choosing an agent, the decision…

机器学习 · 计算机科学 2021-09-27 Gábor Lugosi , Gergely Neu , Julia Olkhovskaya

We study fair resource allocation with strategic agents. It is well-known that, across multiple fundamental problems in this domain, truthfulness and fairness are incompatible. For example, when allocating indivisible goods, no truthful and…

计算机科学与博弈论 · 计算机科学 2024-05-20 Vasilis Gkatzelis , Alexandros Psomas , Xizhi Tan , Paritosh Verma

Finding an envy-free allocation of indivisible resources to agents is a central task in many multiagent systems. Often, non-trivial envy-free allocations do not exist, and, when they do, finding them can be computationally hard. Classical…

计算机科学与博弈论 · 计算机科学 2020-11-24 Robert Bredereck , Andrzej Kaczmarczyk , Rolf Niedermeier

We study mechanisms for an allocation of goods among agents, where agents have no incentive to lie about their true values (incentive compatible) and for which no agent will seek to exchange outcomes with another (envy-free). Mechanisms…

计算机科学与博弈论 · 计算机科学 2010-03-30 Edith Cohen , Michal Feldman , Amos Fiat , Haim Kaplan , Svetlana Olonetsky