Development of a Multiagent Model based on the Development of Distributed Applications

Development of a Multiagent Model based on the Development of Distributed Applications
  IJETT-book-cover           
  
© 2024 by IJETT Journal
Volume-72 Issue-9
Year of Publication : 2024
Author : Abdellah Amine, Rachid Ait Daoud, Fatiha Ait Yacine
DOI : 10.14445/22315381/IJETT-V72I9P105

How to Cite?
Abdellah Amine, Rachid Ait Daoud, Fatiha Ait Yacine, "Development of a Multiagent Model based on the Development of Distributed Applications," International Journal of Engineering Trends and Technology, vol. 72, no. 9, pp. 58-66, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I9P105

Abstract
This strategy aims to automate particular education-related administrative functions. The goal of this automation is to optimize the work carried out in these services by drawing on the theories of distributed artificial intelligence (DAI) and multiagent systems (MAS). In order to do particular tasks, this multiagent application integrates entities known as agents that collaborate and communicate with one another. The Java Agent Development Framework, or JADE middleware, serves as the foundation for the system and is used to develop and manage agents. We have evaluated the multiagent system concept using private data from an experiment we ran with university students.

Keywords
Artificial Intelligence (AI), Distributed Artificial Intelligence (DAI), Multiagent System (MAS), Agent, UML, JADE.

References

[1] Zhang Xue-ling, and MA Chaoqun, “The Employment of Target Administration Theory in the Administration of Teaching Staff in Colleges and Universities,” Journal of Xianyang Teachers College, no. 6, pp. 94-96, 2005.
[Publisher Link]
[2] Robert Allen, Rémi Douence, and David Garlan, “Specifying and Analyzing Dynamic Software Architectures,” Fundamental Approaches to Software Engineering, Lecture Notes in Computer Science, pp. 21-37, 1998.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Michael Wooldridge, An Introduction to Multi Agent Systems, John Wiley & Sons, pp. 1-461, 2009.
[Google Scholar] [Publisher Link]
[4] A. Halberstadt, and L. Mui, “Group and Reputation Modeling in Multi-Agent Systems,” Proceeding Goddard/JPL Workshop on Radical Agents Concepts, NASA Goddard Space Flight Center, 2001.
[Google Scholar]
[5] Thierry Bouron, Jacques Ferber, and Fabien Samuel, “MAGES. A Multi-Agent Testbed for Heterogeneous Agents,” Decentralized Artificial Intelligence, vol. 2, pp. 195-214, 1991.
[Google Scholar]
[6] Alan H. Bond, and Les Gasser, Reading in Distributed Artificial Intelligence, Elsevier Science, pp. 1-668, 1988.
[Google Scholar] [Publisher Link]
[7] Victor R. Lesser, and Daniel G. Corkill, “The Distributed Vehicle Monitoring Testbed: A Tool for Investigating Distributed Problem Solving Network,” AI Magazine, vol. 4, no. 3, pp. 15-33, 1983.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Les Gasser, “Social Conceptions of Knowledge and Action: DAI Foundations and Open Systems Semantics,” Artificial Intelligence, vol. 47, no. 1-3, pp. 107-138, 1991.
[CrossRef] [Google Scholar] [Publisher Link]
[9] C. Baeijs, Y. Demazeau, “Organizations in Multi-Agent Systems,” 4th Days of the GDR PRC IA on Multi-Agent Systems, 1996.
[Google Scholar]
[10] Jaime Simão Sichman, and Rosaria Conte, “On Personal and Role Mental Attitudes: A Preliminary Dependence-Based Analysis,” Advances in Artificial Intelligence, Brazilian Symposium on Artificial Intelligence, pp. 1-10, 1998.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Qingtan Meng, Qian Ma, and Guopeng Zhou, “Distributed Optimization for Nonlinear Multi-Agent Systems with an Upper Triangular Structure” Information Sciences, vol. 641, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Zalimhan Nagoev et al., “Multi-Agent Neurocognitive Architecture of an Intelligent Agent Pattern Recognition System” Procedia Computer Science, vol. 213, pp. 504-509, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Leila Amgoud, Nicolas Maudet, and Simon Parsons, An Argumentation-Based Semantics for Agent Communication Languages, 15th European Conference on Artificial Intelligence, pp. 38-42, 2002.
[Google Scholar] [Publisher Link]
[14] Leila Amgoud, and Simon Parsons, “Agent Dialogues with Conflicting Preferences,” Intelligent Agents VIII, ATAL 2001, Lecture Notes in Computer Science, pp. 190-205, 2002.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Scott A. De Loach, and Mark Wood, “Developing Multiagent Systems with Agent Tool,” Intelligent Agents VII Agent Theories Architectures and Languages, ATAL 2000, Lecture Notes in Computer Science, pp. 46-60, 2001.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Giovanni Caire, and David Cabanillas, “JADE Tutorial: Creating and Using Application Specific Ontologies,” Java Agent Development Framework, pp. 1-30, 2004.
[Google Scholar]
[17] “FIPA ACL Communicative Act Library Specification,” Foundation for Intelligent Physical Agents, Techenical Report, 2002.
[Google Scholar] [Publisher Link]
[18] Jacques Ferber, Multi-Agent Systems towards Collective Intelligence, Inter Editions, pp. 1-522, 1995.
[Google Scholar] [Publisher Link]
[19] Olivier Boissier, Sylvain Gitton, and Pierre Glize, Characteristics of Systems and Applications, Multi-agent Systems/French Observatory of Advanced Techniques, pp. 1-25, 2004.
[Google Scholar] [Publisher Link]
[20] “FIPA ACL Message Structure Specification,” Foundation for Intelligent Physical Agents, Techenical Report, 2002.
[Google Scholar] [Publisher Link]
[21] Christos G. Cassandras, Xu Chu Ding, and Xuchao Lin, “An Optimal Control Approach for the Persistent Monitoring Problem,” 2011 50th IEEE Conference on Decision and Control and European Control Conference, Orlando, FL, USA, pp. 2907-2912, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Morris C. Berenbaum, “Criteria for Analyzing Interactions between Biologically Active Agents,” Advances in Cancer Research, vol. 35, pp. 269-335, 1981.
[CrossRef] [Google Scholar] [Publisher Link]