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Author: Hisashi Hayashi

Affiliation: System Engineering Laboratory, Corporate Research & Development Center and Toshiba Corporation, Japan

Keyword(s): Multi-Agent Systems, Coordination Mechanism, Distributed Task Allocation, Emergency Repair.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Bioinformatics ; Biomedical Engineering ; Cooperation and Coordination ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Methodologies and Technologies ; Multi-Agent Systems ; Operational Research ; Simulation ; Software Engineering ; Symbolic Systems

Abstract: Many distributed systems can be regarded as multi-agent systems (MASs) where some agents are connected to a network but located in different places. We consider severe situations where many causes of future agent failures in MASs are found simultaneously and consecutively owing to large-scale disasters. If a cause of future agent failure is not removed within a limited time, there is a high possibility that one of the agents will stop working. In order to find effective strategies that reduce the number of actual agent failures, we compare some repair-task-allocation strategies for MASs where sensing agents find causes of future agent failures and manager agents communicate with one another to allocate repair tasks to action-execution agents.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Hayashi, H. (2017). Comparing Repair-Task-Allocation Strategies in MAS. In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-219-6; ISSN 2184-433X, SciTePress, pages 17-27. DOI: 10.5220/0006094800170027

@conference{icaart17,
author={Hisashi Hayashi.},
title={Comparing Repair-Task-Allocation Strategies in MAS},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2017},
pages={17-27},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006094800170027},
isbn={978-989-758-219-6},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Comparing Repair-Task-Allocation Strategies in MAS
SN - 978-989-758-219-6
IS - 2184-433X
AU - Hayashi, H.
PY - 2017
SP - 17
EP - 27
DO - 10.5220/0006094800170027
PB - SciTePress