Multivariate algorithmics for eliminating envy by donating goods

IF 2 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Niclas Boehmer, Robert Bredereck, Klaus Heeger, Dušan Knop, Junjie Luo
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Abstract

Fairly dividing a set of indivisible resources to a set of agents is of utmost importance in some applications. However, after an allocation has been implemented the preferences of agents might change and envy might arise. We study the following problem to cope with such situations: given an allocation of indivisible resources to agents with additive utility-based preferences, is it possible to socially donate some of the resources (which means removing these resources from the allocation instance) such that the resulting modified allocation is envy-free (up to one good). We require that the number of deleted resources and/or the caused utilitarian welfare loss of the allocation are bounded. We conduct a thorough study of the (parameterized) computational complexity of this problem considering various natural and problem-specific parameters (e.g., the number of agents, the number of deleted resources, or the maximum number of resources assigned to an agent in the initial allocation) and different preference models, including unary-encoded and 0/1-valuations. In our studies, we obtain a rich set of (parameterized) tractability and intractability results and discover several surprising contrasts, for instance, between the two closely related fairness concepts envy-freeness and envy-freeness up to one good and between the influence of the parameters maximum number and welfare of the deleted resources.

Abstract Image

Abstract Image

通过捐赠物品消除嫉妒的多元算法
在某些应用中,将一组不可分割的资源公平地分配给一组代理至关重要。然而,在实施分配后,代理人的偏好可能会发生变化,并可能产生嫉妒。为了应对这种情况,我们研究了以下问题:给定一个不可分割的资源分配,分配给具有基于效用的加法偏好的代理,那么是否有可能将部分资源进行社会捐赠(这意味着从分配实例中删除这些资源),从而使修改后的分配不引起嫉妒(最多一种物品)。我们要求删除的资源数量和/或分配造成的功利福利损失是有界的。我们对这个问题的(参数化)计算复杂性进行了深入研究,其中考虑了各种自然参数和特定问题参数(如代理人数量、删除资源数量或初始分配中分配给代理人的最大资源数量)以及不同的偏好模型,包括单值编码和 0/1 值。在研究中,我们获得了一系列丰富的(参数化的)可操作性和难操作性结果,并发现了一些令人惊讶的对比,例如,妒忌无忧和妒忌无忧这两个密切相关的公平性概念之间的对比,以及参数最大数量和被删除资源福利之间的对比。
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来源期刊
Autonomous Agents and Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems 工程技术-计算机:人工智能
CiteScore
6.00
自引率
5.30%
发文量
48
审稿时长
>12 weeks
期刊介绍: This is the official journal of the International Foundation for Autonomous Agents and Multi-Agent Systems. It provides a leading forum for disseminating significant original research results in the foundations, theory, development, analysis, and applications of autonomous agents and multi-agent systems. Coverage in Autonomous Agents and Multi-Agent Systems includes, but is not limited to: Agent decision-making architectures and their evaluation, including: cognitive models; knowledge representation; logics for agency; ontological reasoning; planning (single and multi-agent); reasoning (single and multi-agent) Cooperation and teamwork, including: distributed problem solving; human-robot/agent interaction; multi-user/multi-virtual-agent interaction; coalition formation; coordination Agent communication languages, including: their semantics, pragmatics, and implementation; agent communication protocols and conversations; agent commitments; speech act theory Ontologies for agent systems, agents and the semantic web, agents and semantic web services, Grid-based systems, and service-oriented computing Agent societies and societal issues, including: artificial social systems; environments, organizations and institutions; ethical and legal issues; privacy, safety and security; trust, reliability and reputation Agent-based system development, including: agent development techniques, tools and environments; agent programming languages; agent specification or validation languages Agent-based simulation, including: emergent behavior; participatory simulation; simulation techniques, tools and environments; social simulation Agreement technologies, including: argumentation; collective decision making; judgment aggregation and belief merging; negotiation; norms Economic paradigms, including: auction and mechanism design; bargaining and negotiation; economically-motivated agents; game theory (cooperative and non-cooperative); social choice and voting Learning agents, including: computational architectures for learning agents; evolution, adaptation; multi-agent learning. Robotic agents, including: integrated perception, cognition, and action; cognitive robotics; robot planning (including action and motion planning); multi-robot systems. Virtual agents, including: agents in games and virtual environments; companion and coaching agents; modeling personality, emotions; multimodal interaction; verbal and non-verbal expressiveness Significant, novel applications of agent technology Comprehensive reviews and authoritative tutorials of research and practice in agent systems Comprehensive and authoritative reviews of books dealing with agents and multi-agent systems.
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