Tendencies in Multi-Agent Systems: A Systematic Literature Review

The application of Artificial Intelligence mechanisms allows the development of systems capable to solve very complex engineering problems. Multi-agent systems (MAS) are one paradigm that allows an alternative way to design distributed control systems. While research in this area grew exponentially...

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Main Authors: Mariana Falco, Gabriela Robiolo
Format: Article
Language:English
Published: Centro Latinoamericano de Estudios en Informática 2020-04-01
Series:CLEI Electronic Journal
Subjects:
Online Access:https://www.clei.org/cleiej/index.php/cleiej/article/view/456
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spelling doaj-22bd6ee921a64cfc9b894d257667cab32020-11-25T04:00:22ZengCentro Latinoamericano de Estudios en InformáticaCLEI Electronic Journal0717-50002020-04-0123110.19153/cleiej.23.1.1Tendencies in Multi-Agent Systems: A Systematic Literature ReviewMariana Falco0Gabriela RobioloCONICET-LIDTUA(UA) The application of Artificial Intelligence mechanisms allows the development of systems capable to solve very complex engineering problems. Multi-agent systems (MAS) are one paradigm that allows an alternative way to design distributed control systems. While research in this area grew exponentially before 2009, there is a need to understand the status quo of the field from 2009 to June 2017. An extension of the results of a SLR related to Multi-Agent Systems, its applications and research gaps, following Kitchenham and Wholin guidelines are presented in this paper. From the analysis of 279 papers (out of 3522 candidates), our findings suggest that: a) there were 20 gaps related to agent-oriented methodologies; coordination, cooperation and negotiation; modelling, developing, testing and debugging; b) 24 gaps related to specific domains (recycling, dynamic evacuation, hazard management, health-care, industry, logistics and manufacturing, machine learning, ambient assisted living); and 14 gaps related to specific areas within MAS (A-Teams, dynamic MAS and mobile agents, ABMS, evolutionary MAS, and self-organizing MAS). These gaps specify lines of research where the MAS community must work to achieve the unification of the agent-oriented paradigm; as well as strengthen ties with the industry. https://www.clei.org/cleiej/index.php/cleiej/article/view/456Systematic Literature ReviewMulti-Agent SystemsMAS Research GapsAOSE components
collection DOAJ
language English
format Article
sources DOAJ
author Mariana Falco
Gabriela Robiolo
spellingShingle Mariana Falco
Gabriela Robiolo
Tendencies in Multi-Agent Systems: A Systematic Literature Review
CLEI Electronic Journal
Systematic Literature Review
Multi-Agent Systems
MAS Research Gaps
AOSE components
author_facet Mariana Falco
Gabriela Robiolo
author_sort Mariana Falco
title Tendencies in Multi-Agent Systems: A Systematic Literature Review
title_short Tendencies in Multi-Agent Systems: A Systematic Literature Review
title_full Tendencies in Multi-Agent Systems: A Systematic Literature Review
title_fullStr Tendencies in Multi-Agent Systems: A Systematic Literature Review
title_full_unstemmed Tendencies in Multi-Agent Systems: A Systematic Literature Review
title_sort tendencies in multi-agent systems: a systematic literature review
publisher Centro Latinoamericano de Estudios en Informática
series CLEI Electronic Journal
issn 0717-5000
publishDate 2020-04-01
description The application of Artificial Intelligence mechanisms allows the development of systems capable to solve very complex engineering problems. Multi-agent systems (MAS) are one paradigm that allows an alternative way to design distributed control systems. While research in this area grew exponentially before 2009, there is a need to understand the status quo of the field from 2009 to June 2017. An extension of the results of a SLR related to Multi-Agent Systems, its applications and research gaps, following Kitchenham and Wholin guidelines are presented in this paper. From the analysis of 279 papers (out of 3522 candidates), our findings suggest that: a) there were 20 gaps related to agent-oriented methodologies; coordination, cooperation and negotiation; modelling, developing, testing and debugging; b) 24 gaps related to specific domains (recycling, dynamic evacuation, hazard management, health-care, industry, logistics and manufacturing, machine learning, ambient assisted living); and 14 gaps related to specific areas within MAS (A-Teams, dynamic MAS and mobile agents, ABMS, evolutionary MAS, and self-organizing MAS). These gaps specify lines of research where the MAS community must work to achieve the unification of the agent-oriented paradigm; as well as strengthen ties with the industry.
topic Systematic Literature Review
Multi-Agent Systems
MAS Research Gaps
AOSE components
url https://www.clei.org/cleiej/index.php/cleiej/article/view/456
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