article

Fair solutions for some multiagent optimization problems

Authors:

Bruno Escoffier,

Laurent Gourvès,

Jérôme MonnotAuthors Info & Claims

Autonomous Agents and Multi-Agent Systems, Volume 26, Issue 2

Pages 184 - 201

https://doi.org/10.1007/s10458-011-9188-z

Published: 01 March 2013 Publication History

Abstract

We consider optimization problems in a multiagent setting where a solution is evaluated with a vector. Each coordinate of this vector represents an agent's utility for the solution. Due to the possible conflicts, it is unlikely that one feasible solution is optimal for all agents. Then, a natural aim is to find solutions that maximize the satisfaction of the least satisfied agent, where the satisfaction of an agent is defined as his relative utility, i.e., the ratio between his utility for the given solution and his maximum possible utility. This criterion captures a classical notion of fairness since it focuses on the agent with lowest relative utility. We study worst-case bounds on this ratio: for which ratio a feasible solution is guaranteed to exist, i.e., to what extend can we find a solution that satisfies all agents? How can we build these solutions in polynomial time? For several optimization problems, we give polynomial-time deterministic algorithms which (almost always) achieve the best possible ratio.

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Cited By

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Fair solutions for some multiagent optimization problems
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cover image Autonomous Agents and Multi-Agent Systems

Autonomous Agents and Multi-Agent Systems Volume 26, Issue 2

March 2013

174 pages

ISSN:1387-2532

Issue’s Table of Contents

Copyright © Copyright © 2013 The Author(s).

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Kluwer Academic Publishers

United States

Publication History

Published: 01 March 2013

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Cited By

Boes LColley RGrandi ULang JNovaro A(2024)Collective combinatorial optimisation as judgment aggregationAnnals of Mathematics and Artificial Intelligence10.1007/s10472-023-09910-w92:6(1437-1465)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10472-023-09910-w
Li BWu XXu CZhang RWilliams BChen YNeville J(2023)Multiagent MST coverProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i5.25711(5730-5738)Online publication date: 7-Feb-2023
https://dl.acm.org/doi/10.1609/aaai.v37i5.25711
Henrichs ELesch VStraesser MKounev SKrupitzer C(2022)A literature review on optimization techniques for adaptation planning in adaptive systemsInformation and Software Technology10.1016/j.infsof.2022.106940149:COnline publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1016/j.infsof.2022.106940
(2017)Bi-objective matchings with the triangle inequalityTheoretical Computer Science10.1016/j.tcs.2017.01.012670:C(1-10)Online publication date: 29-Mar-2017
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Greco GLang J(2015)Group decision making via weighted propositional logicProceedings of the 24th International Conference on Artificial Intelligence10.5555/2832581.2832669(3008-3014)Online publication date: 25-Jul-2015
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Gourvès LMonnot JTlilane L(2015)Approximate tradeoffs on weighted labeled matroidsDiscrete Applied Mathematics10.1016/j.dam.2014.11.005184:C(154-166)Online publication date: 31-Mar-2015
https://dl.acm.org/doi/10.1016/j.dam.2014.11.005
Elbassioni KNguyen T(2015)Approximation Schemes for Multi-objective Optimization with Quadratic Constraints of Fixed CP-RankProceedings of the 4th International Conference on Algorithmic Decision Theory - Volume 934610.1007/978-3-319-23114-3_17(273-287)Online publication date: 27-Sep-2015
https://dl.acm.org/doi/10.1007/978-3-319-23114-3_17

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