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A COORDINATION LANGUAGE FOR COLLECTIVE AGENT-BASED SYSTEMS: GROUPLOG.

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Title: A COORDINATION LANGUAGE FOR COLLECTIVE AGENT-BASED SYSTEMS: GROUPLOG.
Authors: Barbosa, Fernanda1, Cunha, José C.1
Source: Applied Artificial Intelligence. Jan2001, Vol. 15 Issue 1, p59-78. 20p.
Subjects: Logic machines, Programming languages
Abstract: The paper presents the GroupLog coordination language for collective agent-based systems. It is a logic language based on the notion of group, a cooperating entity whose definition is important to model cooperation in a flexible and well-structured manner and to hide low-level management of coordination activities. In the paper, an informal presentation of the GroupLog language and its use is illustrated through examples. [ABSTRACT FROM AUTHOR]
Copyright of Applied 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: The paper presents the GroupLog coordination language for collective agent-based systems. It is a logic language based on the notion of group, a cooperating entity whose definition is important to model cooperation in a flexible and well-structured manner and to hide low-level management of coordination activities. In the paper, an informal presentation of the GroupLog language and its use is illustrated through examples. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Applied 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.)
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