A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments

5.00
Hdl Handle:
http://hdl.handle.net/10545/621611
Title:
A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments
Authors:
Whitbrook, Amanda ( 0000-0001-8199-0402 ) ; Meng, Qinggang; Chung, Paul W. H.
Abstract:
The aim of this work is to produce and test a robust, distributed, multi-agent task allocation algorithm, as these are scarce and not well-documented in the literature. The vehicle used to create the robust system is the Performance Impact algorithm (PI), as it has previously shown good performance. Three different variants of PI are designed to improve its robustness, each using Monte Carlo sampling to approximate Gaussian distributions. Variant A uses the expected value of the task completion times, variant B uses the worst-case scenario metric and variant C is a hybrid that implements a combination of these. The paper shows that, in simulated trials, baseline PI does not han-dle uncertainty well; the task-allocation success rate tends to decrease linear-ly as degree of uncertainty increases. Variant B demonstrates a worse per-formance and variant A improves the failure rate only slightly. However, in comparison, the hybrid variant C exhibits a very low failure rate, even under high uncertainty. Furthermore, it demonstrates a significantly better mean ob-jective function value than the baseline.
Affiliation:
University of Derby; Loughborough University
Citation:
Whitbrook, A., Meng, Q. and Chung, P. W. H., (2017) “A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments”, in Proceedings, 30th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems(IEA/AIE 2017), Arras, France, June 17- 21.
Issue Date:
27-Jun-2017
URI:
http://hdl.handle.net/10545/621611
Additional Links:
http://www.cril.univ-artois.fr/ieaaie2017/
Type:
Meetings and Proceedings
Language:
en
Sponsors:
EPSRC
Appears in Collections:
Department of Electronics, Computing & Maths

Full metadata record

DC FieldValue Language
dc.contributor.authorWhitbrook, Amandaen
dc.contributor.authorMeng, Qinggangen
dc.contributor.authorChung, Paul W. H.en
dc.date.accessioned2017-05-11T08:32:28Z-
dc.date.available2017-05-11T08:32:28Z-
dc.date.issued2017-06-27-
dc.identifier.citationWhitbrook, A., Meng, Q. and Chung, P. W. H., (2017) “A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments”, in Proceedings, 30th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems(IEA/AIE 2017), Arras, France, June 17- 21.en
dc.identifier.urihttp://hdl.handle.net/10545/621611-
dc.description.abstractThe aim of this work is to produce and test a robust, distributed, multi-agent task allocation algorithm, as these are scarce and not well-documented in the literature. The vehicle used to create the robust system is the Performance Impact algorithm (PI), as it has previously shown good performance. Three different variants of PI are designed to improve its robustness, each using Monte Carlo sampling to approximate Gaussian distributions. Variant A uses the expected value of the task completion times, variant B uses the worst-case scenario metric and variant C is a hybrid that implements a combination of these. The paper shows that, in simulated trials, baseline PI does not han-dle uncertainty well; the task-allocation success rate tends to decrease linear-ly as degree of uncertainty increases. Variant B demonstrates a worse per-formance and variant A improves the failure rate only slightly. However, in comparison, the hybrid variant C exhibits a very low failure rate, even under high uncertainty. Furthermore, it demonstrates a significantly better mean ob-jective function value than the baseline.en
dc.description.sponsorshipEPSRCen
dc.language.isoenen
dc.relation.urlhttp://www.cril.univ-artois.fr/ieaaie2017/en
dc.subjectMulti-agent systemsen
dc.subjectDistributed task allocationen
dc.subjectAuction-based schedulingen
dc.subjectRobustness to uncertaintyen
dc.titleA robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environmentsen
dc.typeMeetings and Proceedingsen
dc.contributor.departmentUniversity of Derbyen
dc.contributor.departmentLoughborough Universityen
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