Robust scheduling and runtime adaptation of multi-agent plan execution

Mingzhong Wang; K Ramamohanarao; J Chen

doi:10.1109/WIIAT.2008.136

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Robust scheduling and runtime adaptation of multi-agent plan execution

Conference paper

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Peer reviewed

Robust scheduling and runtime adaptation of multi-agent plan execution

Mingzhong Wang, K Ramamohanarao and J Chen

Proceedings of the 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), pp.366-372

IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), 2008 (Sydney, Australia, 09-Dec-2008–12-Dec-2008)

IEEE Computer Society

2008

DOI: https://doi.org/10.1109/WIIAT.2008.136

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Abstract

life cycle

scheduling

dynamic environments

execution environments

multi-agent plans

plan evaluations

robust scheduling

run-time

run-time adaptations

simulation results

multi agent systems

Robustness and reliability with respect to the successful completion of a schedule are crucial requirements for scheduling in multi-agent systems because agent autonomy makes execution environments dynamic and nondeterministic. We introduce a model to incorporate trust which indicates the probability that an agent will comply with its commitments into scheduling, thus improving the predicability and stability of the schedule. To deal with exceptions during execution, we adapt and evolve the schedule at runtime by interleaving the processes of evaluation, scheduling, execution and monitoring in the life cycle of a plan. Experiments show that schedules maximizing participants' trust are more likely to survive and succeed in open and dynamic environments. The results also prove that the proposed plan evaluation approach conforms with the simulation result, thus being helpful for plan selection. © 2008 IEEE.

Details

Title: Robust scheduling and runtime adaptation of multi-agent plan execution
Authors: Mingzhong Wang (Author) - University of Melbourne
K Ramamohanarao (Author) - University of Melbourne
J Chen (Author) - University of Melbourne
Contributors: Lakhmi Jain (Editor)
Yuefeng Li (Editor)
Publication details: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), pp.366-372
Conference details: IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), 2008 (Sydney, Australia, 09-Dec-2008–12-Dec-2008)
Publisher: IEEE Computer Society
Date published: 2008
DOI: 10.1109/WIIAT.2008.136
ISBN: 9780769534961
Copyright note: Copyright © 2008 IEEE. Reproduced here in accordance with the publisher's copyright policy. 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.
Organisation Unit: University of the Sunshine Coast, Queensland; USC Business School - Legacy; School of Science, Technology and Engineering
Language: English
Record Identifier: 99449599702621
Output Type: Conference paper

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