research-article

Multi-agent task allocation: learning when to say no

Authors:

Randall ShumakerAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 201 - 208

https://doi.org/10.1145/1389095.1389128

Published: 12 July 2008 Publication History

Abstract

This paper presents a communication-less multi-agent task allocation procedure that allows agents to use past experience to make non-greedy decisions about task assignments. Experimental results are given for problems where agents have varying capabilities, tasks have varying difficulties, and agents are ignorant of what tasks they will see in the future. These types of problems are difficult because the choice an agent makes in the present will affect the decisions it can make in the future. Current task-allocation procedures, especially the market-based ones, tend to side-step the issue by ignoring the future and assigning tasks to agents in a greedy way so that short-term goals are met. It is shown here that these short-sighted allocation procedures work well in situations where the ratio of task length to team size is small, but their performance decreases as this ratio increases. The adaptive method presented here is shown to perform well in a wide range of task-allocation problems, and because it requires no explicit communication, its computational costs are independent of team size.

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Cited By

Guerrero JOliver GValero O(2017)Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and SolutionsPLOS ONE10.1371/journal.pone.017065912:1(e0170659)Online publication date: 24-Jan-2017
https://doi.org/10.1371/journal.pone.0170659
Wicke DFreelan DLuke SWeiss GYolum PBordini RElkind E(2015)Bounty Hunters and Multiagent Task AllocationProceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems10.5555/2772879.2772930(387-394)Online publication date: 4-May-2015
https://dl.acm.org/doi/10.5555/2772879.2772930
Sen SAdams J(2015)An influence diagram based multi-criteria decision making framework for multirobot coalition formationAutonomous Agents and Multi-Agent Systems10.1007/s10458-014-9276-y29:6(1061-1090)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1007/s10458-014-9276-y
Show More Cited By

Index Terms

Multi-agent task allocation: learning when to say no
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Guerrero JOliver GValero O(2017)Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and SolutionsPLOS ONE10.1371/journal.pone.017065912:1(e0170659)Online publication date: 24-Jan-2017
https://doi.org/10.1371/journal.pone.0170659
Wicke DFreelan DLuke SWeiss GYolum PBordini RElkind E(2015)Bounty Hunters and Multiagent Task AllocationProceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems10.5555/2772879.2772930(387-394)Online publication date: 4-May-2015
https://dl.acm.org/doi/10.5555/2772879.2772930
Sen SAdams J(2015)An influence diagram based multi-criteria decision making framework for multirobot coalition formationAutonomous Agents and Multi-Agent Systems10.1007/s10458-014-9276-y29:6(1061-1090)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1007/s10458-014-9276-y
Vasudevan MTian YTang MKozan E(2014)Profiling: An application assignment approach for green data centersIECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society10.1109/IECON.2014.7049325(5400-5406)Online publication date: Oct-2014
https://doi.org/10.1109/IECON.2014.7049325
Guerrero JOliver G(2012)Multi-robot coalition formation in real-time scenariosRobotics and Autonomous Systems10.1016/j.robot.2012.06.00460:10(1295-1307)Online publication date: 1-Oct-2012
https://dl.acm.org/doi/10.1016/j.robot.2012.06.004
Guerrero JOliver G(2012)Swarm-like Methodologies for Executing Tasks with DeadlinesJournal of Intelligent and Robotic Systems10.1007/s10846-012-9666-968:1(3-19)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/s10846-012-9666-9
Rohrmüller FWollherr DBuss M(2012)MuRoCo: A Framework for Capability- and Situation-Aware Coalition Formation in Cooperative Multi-Robot SystemsJournal of Intelligent & Robotic Systems10.1007/s10846-012-9654-067:3-4(339-370)Online publication date: 29-Feb-2012
https://doi.org/10.1007/s10846-012-9654-0

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