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A component-based multi-agent system...
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Lian, Jiexin.
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A component-based multi-agent system modeling methodology.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
A component-based multi-agent system modeling methodology./
Author:
Lian, Jiexin.
Description:
128 p.
Notes:
Adviser: Sol M. Shatz.
Contained By:
Dissertation Abstracts International68-12B.
Subject:
Artificial Intelligence. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3294334
ISBN:
9780549391968
A component-based multi-agent system modeling methodology.
Lian, Jiexin.
A component-based multi-agent system modeling methodology.
- 128 p.
Adviser: Sol M. Shatz.
Thesis (Ph.D.)--University of Illinois at Chicago, 2007.
Software agents and Multi-Agent Systems (MAS) have attracted significant research and development attention during the past decade. Coordination, the process by which agents reason about and manage the interdependences among their behaviors and try to ensure that all members of the system act consistently, is critical in the MAS design. Due to the ubiquitous existence of conflicts in MAS, conflict control is essential for coordinated agent behavior. To support the creation of MAS models that provide flexible coordination and conflict control, this dissertation defines a new feature called a potential arc that is used to extend traditional Colored Petri Net (CPN) models to support agent behavior modeling. Potential arcs serve to extend the traditional CPN model with an explicit support for distinguishing the representation of potential conflicts and real conflicts, and thereby avoid the need for eliminating all potential conflicts in the design stage.
ISBN: 9780549391968Subjects--Topical Terms:
769149
Artificial Intelligence.
A component-based multi-agent system modeling methodology.
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A component-based multi-agent system modeling methodology.
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128 p.
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Adviser: Sol M. Shatz.
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Source: Dissertation Abstracts International, Volume: 68-12, Section: B, page: 8137.
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Thesis (Ph.D.)--University of Illinois at Chicago, 2007.
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Software agents and Multi-Agent Systems (MAS) have attracted significant research and development attention during the past decade. Coordination, the process by which agents reason about and manage the interdependences among their behaviors and try to ensure that all members of the system act consistently, is critical in the MAS design. Due to the ubiquitous existence of conflicts in MAS, conflict control is essential for coordinated agent behavior. To support the creation of MAS models that provide flexible coordination and conflict control, this dissertation defines a new feature called a potential arc that is used to extend traditional Colored Petri Net (CPN) models to support agent behavior modeling. Potential arcs serve to extend the traditional CPN model with an explicit support for distinguishing the representation of potential conflicts and real conflicts, and thereby avoid the need for eliminating all potential conflicts in the design stage.
520
$a
Based on the potential arc concept, this dissertation presents a MAS modeling methodology. In order to provide a foundation for the automation of MAS modeling, this report extends the formal definition of Colored Petri Net (CPN) to design a Potential Colored Petri Net (PCPN). The design of our modeling methodology embraces the principle of "separation of concerns" in agent-oriented design, and focuses on modeling the possible behaviors of the MAS.
520
$a
The research reported in this dissertation involves a broad array of tasks, including model generation algorithms, analysis/simulation techniques, and experimentation. The main contributions of the research are: (1) defines a new feature called a potential arc that is used to extend traditional Colored Petri Net (CPN) models to support agent behavior modeling; (2) presents a semi-automated MAS modeling methodology, which allow software engineers to create MAS systems based on the extended CPN model; (3) presents an intelligent coordinator design methodology, resulting in a set of coordinators at different levels of intelligence; and (4) evaluates the proposed modeling methodology by developing models and performing simulation-based analysis.
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University of Illinois at Chicago.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3294334
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