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Multi-agent cooperation pursuit based on an extension of AALAADIN organisational model.

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Title: Multi-agent cooperation pursuit based on an extension of AALAADIN organisational model.
Authors: Souidi, Mohammed El Habib1 (AUTHOR) mohamed.souidi@hit.edu.cn, Songhao, Piao1 (AUTHOR), Guo, Li1 (AUTHOR), Lin, Chang1 (AUTHOR)
Source: Journal of Experimental & Theoretical Artificial Intelligence. Dec2016, Vol. 28 Issue 6, p1075-1088. 14p.
Subjects: Multiagent systems, Cooperative processing, Markov processes, Problem solving, Fuzzy logic
Abstract: An approach of cooperative pursuit for multiple mobile targets based on multi-agents system is discussed. In this kind of problem the pursuit process is divided into two kinds of tasks. The first one (coalition problem) is designed to solve the problem of the pursuit team formation. To achieve this mission, we used an innovative method based on a dynamic organisation and reorganisation of the pursuers’ groups. We introduce our coalition strategy extended from the organisational agent, group, role model by assigning an access mechanism to the groups inspired by fuzzy logic principles. The second task (motion problem) is the treatment of the pursuers’ motion strategy. To manage this problem we applied the principles of the Markov decision process. Simulation results show the feasibility and validity of the given proposal. [ABSTRACT FROM PUBLISHER]
Copyright of Journal of Experimental & Theoretical Artificial Intelligence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Multi-agent cooperation pursuit based on an extension of AALAADIN organisational model.
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  Data: <searchLink fieldCode="AR" term="%22Souidi%2C+Mohammed+El+Habib%22">Souidi, Mohammed El Habib</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mohamed.souidi@hit.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Songhao%2C+Piao%22">Songhao, Piao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guo%2C+Li%22">Guo, Li</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lin%2C+Chang%22">Lin, Chang</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Experimental+%26+Theoretical+Artificial+Intelligence%22">Journal of Experimental & Theoretical Artificial Intelligence</searchLink>. Dec2016, Vol. 28 Issue 6, p1075-1088. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Multiagent+systems%22">Multiagent systems</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperative+processing%22">Cooperative processing</searchLink><br /><searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+logic%22">Fuzzy logic</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: An approach of cooperative pursuit for multiple mobile targets based on multi-agents system is discussed. In this kind of problem the pursuit process is divided into two kinds of tasks. The first one (coalition problem) is designed to solve the problem of the pursuit team formation. To achieve this mission, we used an innovative method based on a dynamic organisation and reorganisation of the pursuers’ groups. We introduce our coalition strategy extended from the organisational agent, group, role model by assigning an access mechanism to the groups inspired by fuzzy logic principles. The second task (motion problem) is the treatment of the pursuers’ motion strategy. To manage this problem we applied the principles of the Markov decision process. Simulation results show the feasibility and validity of the given proposal. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Experimental & Theoretical Artificial Intelligence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=118480967
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        Value: 10.1080/0952813X.2015.1056241
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        Text: English
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        PageCount: 14
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        Type: general
      – SubjectFull: Cooperative processing
        Type: general
      – SubjectFull: Markov processes
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      – SubjectFull: Problem solving
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      – SubjectFull: Fuzzy logic
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            – D: 01
              M: 12
              Text: Dec2016
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