A Novel Deep Learning Approach for Semantic Interoperability Between Heteregeneous Multi-Agent Systems


  • N. El Abid Amrani SSDIA Laboratory, ENSET Mohammedia, Hassan II University, Morocco
  • O. El Kheir Abra SSDIA Laboratory, ENSET Mohammedia, Hassan II University, Morocco
  • M. Youssfi University of Hassan II Casablanca, Morocco
  • O. Bouattane University of Hassan II Casablanca, Morocco
Volume: 9 | Issue: 4 | Pages: 4566-4573 | August 2019 | https://doi.org/10.48084/etasr.2841


This article focuses on the issue of semantic interoperability in heterogeneous distributed multi-agent systems. Existing middleware technologies offer programming models that strongly combine agents’ learning models and communication models, which can lead to performance weaknesses when the number of agents is very important. Moreover, existing methods in the field of semantic interoperability solve the problem of understanding messages exchanged between distributed agents with heterogeneous ontologies, using several techniques to combine these ontologies. The first category of these methods relies on the fusion principle, others use alignment, and finally, there are those founded on Semantic Web technique. All these methods are limited to abstract concepts and do not deal with concrete concepts such as those represented by images. We propose in this paper a new approach that addresses the problem of semantic interoperability between heterogeneous distributed agents based on two principles: At first, the communication aspect of the agent from the learning aspect is separated. Then, we propose extending semantic interoperability to concrete concepts by combining two techniques: Semantic Web technology, which allows terms representing abstract concepts to be interpreted and deep learning technology, which is introduced as a new method to ensure semantic interoperability in the case of concrete concepts such as images. A detailed description of the proposed approach is provided, showing that it is very useful in solving the disadvantages of existing multi-agent platforms.


multi-agent system, middleware, semantic interoperability, ontology, web semantic, deep learning


Download data is not yet available.


A. Shajjar, N. Khalid, H. F. Ahmad, H. Sugun, “Service Interoperability between Agents and Semantic Web Services for Nomadic Environment”, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Sydney, Australia, December 9-12, 2008 DOI: https://doi.org/10.1109/WIIAT.2008.327

V. M. Ionescu, “The analysis of the performance of RabbitMQ and ActiveMQ”, 14th RoEduNet International Conference - Networking in Education and Research, Net NER), Craiova, Romania, September 24-26, 2015 DOI: https://doi.org/10.1109/RoEduNet.2015.7311982

A. F. Klein, M. Stefanescu, A. Saied, K. Swakhoven, “An experimental comparison of ActiveMQ and OpenMQ brokers in asynchronous cloud environment”, 5th International Conference on Digital Information Processing and Communications, Sierre, Switzerland, October 7-9, 2015 DOI: https://doi.org/10.1109/ICDIPC.2015.7323001

H. Suguri, E. Kodama, M. Miyazaki, I. Kaji, “Assuring interoperability between heterogeneous multi-agent systems with a gateway agent”, 7th IEEE International Symposium on High Assurance Systems Engineering, Tokyo, Japan, October 23-25, 2002

N. E. A. Amrani, M. Youssfi, O. E. K. Abra, “Semantic interoperability between heterogeneous multi-agent systems based on Deep Learning”, 6th International Conference on Multimedia Computing and Systems, Rabat, Morocco, May 10-12, 2018 DOI: https://doi.org/10.1109/ICMCS.2018.8525921

E. J. Gonzalez, A. Hamilton, L. Moreno, R. L. Marichal, J. A. Mendez, V. Munoz, “Development of a multiagent system for identification and control”, IEEE Conference on Emerging Technologies and Factory Automation, Catania, Italy, September 19-22, 2005

D. Camacho, R. Aler, C. Castro, J. M. Molina, “Performance evaluation of ZEUS, Jade, and SkeletonAgent frameworks”, IEEE International Conference on Systems, Man and Cybernetics, Yasmine Hammamet, Tunisia, October 6-9, 2002

M. Mohsenzadeh, F. S. Aliee, M. Teshnehlab, “A New Approach for Merging Ontologies”, World Academy of Science, Engineering and Technology, Vol. 4, pp.647-653, 2007

H. Kong, M. Hwang, P. Kim, “A new methodology for merging the heterogeneous domain ontologies based on the WordNet”, International Conference on Next Generation Web Services Practices, Seoul, South Korea, August 22-26, 2005

S. C. Bailin, W. Truszkowski, “Cooperation Between Intelligent Information Agents”, in: Lecture Notes in Computer Science, Vol. 2182, Springer, 2001 DOI: https://doi.org/10.1007/3-540-44799-7_24

C. R. R. Robin, G. V. Uma, “A Novel Algorithm for Fully Automated Ontology Merging Using Hybrid Strategy”, European Journal of Scientific Research, Vol. 47. No. 1, pp. 74-81, 2010

S. Bailin, W. Truszkowski, “Ontology negotiation: How agents can really get to know each other”, in: Lecture Notes in Computer Science, Vol. 2564, Springer, 2003 DOI: https://doi.org/10.1007/978-3-540-45173-0_24

J. Li, J. Tang, Y. Li, Q. Luo, “RiMOM: A Dynamic Multistrategy Ontology Alignment Framework”, IEEE Transactions on Knowledge and Data Engineering, Vol. 21, No. 8, pp. 1218-1232, 2009 DOI: https://doi.org/10.1109/TKDE.2008.202

J. Euzenat, A. Polleres, F. Scharffe, “Processing Ontology Alignments with SPARQL”, International Conference on Complex, Intelligent and Software Intensive Systems, Barcelona, Spain, March 4-7, 2008 DOI: https://doi.org/10.1109/CISIS.2008.126

N. Vlassis, A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence, Morgan & Claypool, 2007 DOI: https://doi.org/10.2200/S00091ED1V01Y200705AIM002

T. Agotnes, W. Van der Hoek, M. Wooldridge, “Quantified coalition logic”, Synthese, Vol. 165, No. 2, pp. 269-294, 2008 DOI: https://doi.org/10.1007/s11229-008-9363-1

S. Willmott, F. O. F. Pena, C. Merida-Campos, I. Constantinescu, J. Dale, D. Cabanillas, “Adapting agent communication languages for semantic Web service inter-communication”, The 2005 IEEE/WIC/ACM International Conference on Web Intelligence, Compiegne, France, September 19-25, 2005

X. Jin, “Ontology-based software agent for intelligent business terminal”, 2nd IEEE International Conference on Information Management and Engineering, Chengdu, China, April 16-18, 2010 DOI: https://doi.org/10.1109/ICIME.2010.5478214

D. Fensel, J. A. Hendler, H. Lieberman; W. Wahlster, T. Berners-Lee, “Languages and Ontologies”, in: Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential, The MIT Press, 2005 DOI: https://doi.org/10.7551/mitpress/6412.001.0001

B. Abrahams, W. Dai, “Architecture for automated annotation and ontology based querying of semantic Web resources”, The 2005 IEEE/WIC/ACM International Conference on Web Intelligence, Compiegne, France, September 19-25, 2005

A. Gudi, H. E. Tasli, T. M. den Uyl, A. Maroulis, “Deep learning based FACS Action Unit occurrence and intensity estimation”, 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), Ljubljana, Slovenia, May 4-8, 2015 DOI: https://doi.org/10.1109/FG.2015.7284873

A. A. M. Al-Saffar, H. Tao, M. A. Talab, “Review of deep convolution neural network in image classification”, 2017 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, Jakarta, Indonesia, October 23-24, 2017 DOI: https://doi.org/10.1109/ICRAMET.2017.8253139


How to Cite

N. El Abid Amrani, O. El Kheir Abra, M. Youssfi, and O. Bouattane, “A Novel Deep Learning Approach for Semantic Interoperability Between Heteregeneous Multi-Agent Systems”, Eng. Technol. Appl. Sci. Res., vol. 9, no. 4, pp. 4566–4573, Aug. 2019.


Abstract Views: 494
PDF Downloads: 330

Metrics Information

Most read articles by the same author(s)