Developing a multi-agent model for distributed knowledge systems

Author(s):  
D. Cho ◽  
F. Kusunoki ◽  
S. Ono ◽  
T. Terano
2011 ◽  
pp. 233-261 ◽  
Author(s):  
Davy Monticolo ◽  
Vincent Hilaire ◽  
Samuel Gomes ◽  
Abderrafiaa Koukam

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. In the mechanical design domain, the KM facilitates the design of routine product and brings a saving time for innovation. This chapter describes the specification of a project memory as an organizational memory to specify knowledge to capitalize all along project in order to be reuse. Afterwards it presents the design of a domain ontology and a multi agent system to manage project memories all along professional activities. As a matter of fact, these activities require that engineers, with different specialities, collaborate to carry out the same goal. Inside professional activities; they use their knowhow and knowledge in order to achieve the laid down goals. The professional actors competences and knowledge modeling allows the design and the description of agents’ know-how. Furthermore, the paper describes the design of our agent model based on an organisational approach and the role of a domain ontology called OntoDesign to manage heterogeneous and distributed knowledge.


2009 ◽  
pp. 244-269 ◽  
Author(s):  
Davy Monticolo ◽  
Vincent Hilaire ◽  
Samuel Gomes ◽  
Abderrafiaa Koukam

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. In the mechanical design domain, the KM facilitates the design of routine product and brings a saving time for innovation. This chapter describes the specification of a project memory as an organizational memory to specify knowledge to capitalize all along project in order to be reuse. Afterwards it presents the design of a domain ontology and a multi agent system to manage project memories all along professional activities. As a matter of fact, these activities require that engineers, with different specialities, collaborate to carry out the same goal. Inside professional activities; they use their knowhow and knowledge in order to achieve the laid down goals. The professional actors competences and knowledge modeling allows the design and the description of agents’ know-how. Furthermore, the paper describes the design of our agent model based on an organisational approach and the role of a domain ontology called OntoDesign to manage heterogeneous and distributed knowledge.


Author(s):  
О. Z. Mintser ◽  
О. Ye. Stryzhak ◽  
S. V. Denysenko

<p class="a0">Approaches, facilities and technologies of forming of the personalized electronic grounds of management in the educational- informative environment knowledge are described. The ontological aspects of model scenario construction in doctor’s education post-graduate training accompaniment are considered with the use of the network systems of knowledge. It supposes the decision of increasing of efficiency medical educating of doctors on application of modern network technologies of the distance access to t h e distributed knowledge systems.</p>


2009 ◽  
Vol 29 (2) ◽  
pp. 412-415
Author(s):  
Qiang LU ◽  
Ming CHEN ◽  
Zhi-guang WANG

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4873
Author(s):  
Biao Xu ◽  
Minyan Lu ◽  
Hong Zhang ◽  
Cong Pan

A wireless sensor network (WSN) is a group of sensors connected with a wireless communications infrastructure designed to monitor and send collected data to the primary server. The WSN is the cornerstone of the Internet of Things (IoT) and Industry 4.0. Robustness is an essential characteristic of WSN that enables reliable functionalities to end customers. However, existing approaches primarily focus on component reliability and malware propagation, while the robustness and security of cascading failures between the physical domain and the information domain are usually ignored. This paper proposes a cross-domain agent-based model to analyze the connectivity robustness of a system in the malware propagation process. The agent characteristics and transition rules are also described in detail. To verify the practicality of the model, three scenarios based on different network topologies are proposed. Finally, the robustness of the scenarios and the topologies are discussed.


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