Agent-based Semantic Negotiation Protocol for Semantic Heterogeneity Solving in Multi-agent System

Dhouha Ben Noureddine, Atef Gharbi, Samir ben Ahmed

2017

Abstract

In this article, we propose an interactive agent model in an open and heterogeneous multi-agent system (MAS). Our model allows agents to autonomously communicate between each other through semantic heterogeneity. The communication problem can be expressed by the calculation based on the abilities acquired in the receiver agent, compared to the message sent by the sender agent. Hence, the semantic heterogeneity should be resolved in the message processing. The agent can autonomously enrich its own ontology by using semantic negotiation approach in several steps. We develop firstly, a model using an ontology alignment framework. Then, we enhance a similarity measure to select the most similar pairs by combining a psychological knowledge of the relevance, the resemblance, and the non-symmetry of similarity. At the end, we suggest a protocol for supporting semantic negotiation. In order to explain our approach, we implement a simple benchmark production system on JADE.

References

  1. Bellifemine, F., Caire, G., and Greenwood, D. (2007). Developing multi-agent systems with jade.
  2. Ben Noureddine, D., Gharbi, A., and Ben Ahmed, S. (2016). An approach for multi-robot system based on agent layered architecture. In Proc. of the 87th International Conference on Artificial Intelligence and Soft Computing (ICAISC'16), Lasbone, Portugal, pages 1- 9.
  3. Bordini, R. e. a. (2006). A survey of programming languages and platforms for multi-agent systems. Informatica, 30(1):33-44.
  4. Chuan-Jun, S. (2011). Jade implemented mobile multiagent based, distributed information platform for pervasive health care monitoring. Applied Soft Computing, 11(1):315-325.
  5. Comi, A., Fotia, L., Messina, F., Pappalardo, G., Rosaci, D., and Sarne, G. M. (2015). Using semantic negotiation for ontology enrichment in e-learning multi agent systems. In Ninth International Conference on Complex, Intelligent, and Software Intensive Systems, pages 474-479.
  6. David, J., Euzenat, J., Scharffe, F., and Trojahn dos Santos, C. (2011). The alignment api 4.0. Semantic web journal, 2(1):3-10.
  7. De Meo, P., Quattrone, G., Rosaci, D., and Ursino, D. (2012). Bilateral semantic negotiation: a decentralised approach to ontology enrichment in open multiagent systems. International Journal of Data Mining, Modelling and Management, 4(1):1-38.
  8. Euzenat, J. (2013). An api for ontology alignment. Springer-Verlag, pages 698-712.
  9. Garruzzo, S., Quattrone, G., Rosaci, D., and Ursino, D. (2011). Improving agent interoperability via the automatic enrichment of multi-category ontologies. Web Intelligence and Agent Systems, 9(4):291-318.
  10. Garruzzo, S. and Rosaci, D. (2008). Agent clustering based on semantic negotiation. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 3(2):7.
  11. Hruz, B. and Zhou, M. (2007). Modeling and control of discrete-event dynamic systems with petri nets and other tools. Springer, page 67.
  12. Laera, L., Blacoe, I., Tamma, V., Payne, T.and Euzenat, J., and Bench-Capon, T. (2007). Argumentationove ontology correspondances in mas. In 6th international joint conference on Autonomous Agents and MultiAgent Systems (AAMAS'07), pages 1285-1292.
  13. Maes, P. (1994). Agents that reduce workload and information overload. Communications of the ACM, 37(7):30-40.
  14. Messina, F., Pappalardo, G., Pappalardo, C., Santoro, D., Rosaci, G., and L., S. G. M. (2014). An agent based negotiation protocol for cloud service level agreements. In 2014 IEEE 23rd International In WETICE Conference (WETICE), pages 161-166.
  15. Morge, M. and Routier, J. (2007). Debating over heterogeneous descriptions. Applied Ontology, 2:333-349.
  16. Salvatore, V. and Vincenzo, C. (2009). An extended jade-s based framework for developing secure multiagent systems. Computer Standards & Interfaces, 31(5):913-930.
  17. Shvaiko, P. and Euzenat, J. (2013). Ontology matching: State of the art and future challenges. IEEE Transactions on knowledge and data engineering, 25:158-176.
  18. Tversky, A. (1977). Features of similarity. Psychological Review, pages 327-352.
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Paper Citation


in Harvard Style

Ben Noureddine D., Gharbi A. and ben Ahmed S. (2017). Agent-based Semantic Negotiation Protocol for Semantic Heterogeneity Solving in Multi-agent System . In Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-250-9, pages 247-254. DOI: 10.5220/0006344602470254


in Bibtex Style

@conference{enase17,
author={Dhouha Ben Noureddine and Atef Gharbi and Samir ben Ahmed},
title={Agent-based Semantic Negotiation Protocol for Semantic Heterogeneity Solving in Multi-agent System},
booktitle={Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2017},
pages={247-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006344602470254},
isbn={978-989-758-250-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Agent-based Semantic Negotiation Protocol for Semantic Heterogeneity Solving in Multi-agent System
SN - 978-989-758-250-9
AU - Ben Noureddine D.
AU - Gharbi A.
AU - ben Ahmed S.
PY - 2017
SP - 247
EP - 254
DO - 10.5220/0006344602470254