Developing Multi Agent Systems on Semantic Web Environment Using SEAGENT Platform

In this chapter, the authors describe the relationships between multi-agent systems, social networks, and the Semantic Web within collaborative work; they also review how the integration of multi-agent systems and Semantic Web technologies and techniques can be used to enhance social networks at all scales. The chapter first provides a review of relevant work on the application of agent-based models and abstractions to the key ingredients of our work: collaborative systems, the Semantic Web, and social networks. Then, the chapter discusses the reasons current multi-agent systems and their foreseen evolution might be a fundamental means for the realization of the future Semantic Social Networks. Finally, some conclusions are drawn.

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Developing an Intelligent Parking Management Application Based on Multi-agent Systems and Semantic Web Technologies

Lecture Notes in Computer Science - Hybrid Artificial Intelligence Systems ◽

10.1007/978-3-642-13769-3_8 ◽

2010 ◽

pp. 64-72 ◽

Cited By ~ 1

Author(s):

Andrés Muñoz ◽

Juan A. Botía

Keyword(s):

Semantic Web ◽

Multi Agent Systems ◽

Semantic Web Technologies ◽

Web Technologies ◽

Agent Systems ◽

Management Application ◽

Parking Management ◽

Multi Agent

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A multi-agent based system with big data processing for enhanced supply chain agility

Journal of Enterprise Information Management ◽

10.1108/jeim-06-2015-0050 ◽

2016 ◽

Vol 29 (5) ◽

pp. 706-727 ◽

Cited By ~ 53

Author(s):

Mihalis Giannakis ◽

Michalis Louis

Keyword(s):

Big Data ◽

Supply Chain ◽

Semantic Web ◽

Supply Chains ◽

Multi Agent Systems ◽

Content Type ◽

Agent Based ◽

Agent Systems ◽

Supply Chain Agility ◽

Multi Agent

Purpose Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored. Design/methodology/approach For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled. Findings Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility. Research limitations/implications The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems. Practical implications The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis. Originality/value A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.

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