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A novel distributed scheduling algorithm for time-critical multi-agent systems

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conference contribution
posted on 2015-09-23, 14:52 authored by Amanda Whitbrook, Qinggang MengQinggang Meng, Paul Chung
This paper describes enhancements made to the distributed performance impact (PI) algorithm and presents the results of trials that show how the work advances the stateof- the-art in single-task, single-robot, time-extended, multiagent task assignment for time-critical missions. The improvement boosts performance by integrating the architecture with additional action selection methods that increase the exploratory properties of the algorithm (either soft max or ε-greedy task selection). It is demonstrated empirically that the average time taken to perform rescue tasks can reduce by up to 8% and solution of some problems that baseline PI cannot handle is enabled. Comparison with the consensusbased bundle algorithm (CBBA) also shows that both the baseline PI algorithm and the enhanced versions are superior. All test problems center around a team of heterogeneous, autonomous vehicles conducting rescue missions in a 3- dimensional environment, where a number of different tasks must be carried out in order to rescue a known number of victims that is always more than the number of available vehicles.

Funding

This work was supported by EPSRC (grant number EP/J011525/1) with BAE Systems as the leading industrial partner.

History

School

  • Science

Department

  • Computer Science

Published in

IROS 2015

Citation

WHITBROOK, A., MENG, Q. and CHUNG, P.W.H., 2015. A novel distributed scheduling algorithm for time-critical multi-agent systems. Presented at: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, 28th Sept. to 2nd Oct. pp.6451-6488.

Publisher

IEEE

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Language

  • en

Location

Hamburg, Germany

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