A MAS-BASED NEGOTIATION MECHANISM TO DEAL WITH SATURATED CONDITIONS IN DISTRIBUTED ENVIRONMENTS

Mauricio Paletta, Pilar Herrero

2010

Abstract

In Collaborative Distributed Environments (CDEs) based on Multi-Agent System (MAS), agents collaborate with each other aiming to achieve a common goal. However, depending on several aspects, like for example the number of nodes in the CDE, the environment condition could be saturated / overloaded making it difficult for agents who are requesting the cooperation of others to carry out its tasks. To deal with this problem, the MAS-based solution should have an appropriate negotiation mechanism between agents. Appropriate means to be efficient in terms of the time involved in the entire process and, of course, that the negotiation is successful. This paper focuses on this problem by presenting a negotiation mechanism (algorithm and protocol) designed to be used in CDEs by means of multi-agent architecture and the awareness concept. This research makes use of a heuristic strategy in order to improve the effectiveness of agents’ communication resources and therefore improve collaboration in these environments.

References

  1. Andre, D., Koza, J., 1996. A parallel implementation of genetic programming that achieves super-linear performance. In Proc. International Conference on Parallel and Distributed Processing Techniques and Applications, pp. 1163-1174.
  2. Arenas, M.I., Collet, P., Eiben, A.E., Jelasity, M., Merelo, J.J., Paechter, B., Preuss, M., Schoenauer M., 2002. A Framework for Distributed Evolutionary Algorithms. In Proc. 7th International Conference on Parallel Problem Solving from Nature (PPSN VII). LNCS 2439, pp. 665-675.
  3. Bellifemine, F., Poggi, A. Rimassa, G., 1999. JADE - A FIPA-compliant agent framework. Telecom Italia internal technical report. In Proc. International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAM'99), pp. 97-108.
  4. Blanchard, E., Frasson, C., 2002. Designing a Multi-agent Architecture based on Clustering for Collaborative Learning Sessions. In Proc. International Conference in Intelligent Tutoring Systems, LNCS. Springer.
  5. Greenhalgh C., 1997. Large Scale Collaborative Virtual Environments. Doctoral Thesis, University of Nottingham.
  6. Ferber, J., 1995. Les systems multi-agents, Vers une intelligence collective. Ed. InterEditions, pp. 1-66.
  7. Kohonen, T., Mäkisara, K., Saramäki, T., 1984. Phonotopic maps - insightful representation of phonological features for speech recognition. In Proc. 7th International Conference on Pattern Recognition, pp. 182-185.
  8. Lin, F., Lin, Y., 2006. Integrating multi-agent negotiation to resolve constraints in fulfilling supply chain orders Electronic Commerce Research and Applications, Vol. 5, No. 4, pp. 313-322.
  9. Makhoul, J., Roucos, S., Gish, H., 1985. Vector quantization in speech coding. In Proc. IEEE 73, IEEE Computer Society, pp. 1551-1588.
  10. Martinetz, T.M., Schulten, K.J., 1991. A neural-gas network learns topologies. In T. Kohonen et al (eds)., Artificial Neural Networks, pp. 397-402.
  11. Mayrhofer, R., Radi, H., 2007. Extending the Growing Neural Gas Classifier for Context Recognition. Computer Aided Systems Theory - EUROCAST 2007, pp. 920-927.
  12. Nasrabadi, N.M., Feng, Y., 1988. Vector quantization of images based upon the Kohonen self-organizing feature maps. In IEEE International Conference on Neural Networks, pp. 1101-1108.
  13. Nasrabadi, N.M., King, R.A., 1988. Image coding using vector quantization: A review. IEEE Trans Comm 36(8), IEEE Computer Society, pp. 957-971.
  14. Naylor, J., Li, K.P., 1988. Analysis of a Neural Network Algorithm for vector quantization of speech parameters. In Proc. First Annual INNS Meeting, NY, Pergamon Press, pp. 310-315.
  15. Oprea, M., 2002. An Adaptive Negotiation Model for Agent-Based Electronic Commerce. Studies in Informatics and Control, Vol. 11 i3, pp. 271-279.
  16. Paletta, M., Herrero, P., 2008. Learning Cooperation in Collaborative Grid Environments to Improve Cover Load Balancing Delivery. In Proc. IEEE/WIC/ACM Joint Conferences on Web Intelligence and Intelligent Agent Technology, pp. 399-402.
  17. Paletta, M., Herrero P., 2009. Awareness-based Learning Model to Improve Cooperation in Collaborative Distributed Environments. In Proc. 3rd International KES Symposium on Agents and Multi-agents Systems - Technologies and Applications (KES-AMSTA 2009), LNAI 5559, Springer, pp. 793-802.
  18. Paletta, M., Herrero P., 2009. Foreseeing Cooperation Behaviors in Collaborative Grid Environments. In Proc. 7th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS'09), Vol. 50/2009, Springer, pp 120-129.
  19. Paletta M., Herrero P., 2009. Towards Fraud Detection Support using Grid Technology, Special Issue at Multiagent and Grid Systems - An International Journal, Vol. 5, No. 3, IOS Press, pp. 311-324.
  20. Roussaki, I., Papaioannou, I. Anangostou, M., 2007. Building Automated Negotiation Strategies Enhanced by MLP and GR Neural Networks for Opponent Agent Behaviour Prognosis. Computational and Ambient Intelligence, V. 4507, Springer, pp. 152-161.
  21. Sakas, D.P., Vlachos, D.S., Simos, T.E., 2007. Adaptive Neural Networks for Automatic Negotiation. In Proc. of the International Conference on Computational Methods in Science and Engineering (ICCMSE 2007), Vol. 2, Parts A and B, AIP Conference Proceedings, pp. 1355-1358.
  22. Wooldridge., M.J., 2002. An Introduction to Multiagent Systems, John Wiley and Sons.
  23. Zeng, Z.M., Meng, B., Zeng, Y.Y., 2005. An Adaptive Learning Method in Automated Negotiation Based on Artificial Neural Network. In Proc. of 2005 International Conference on Machine Learning and Cybernetics, Vol. 1, Issue 18-21, pp. 383-387.
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Paper Citation


in Harvard Style

Paletta M. and Herrero P. (2010). A MAS-BASED NEGOTIATION MECHANISM TO DEAL WITH SATURATED CONDITIONS IN DISTRIBUTED ENVIRONMENTS . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-674-022-1, pages 159-164. DOI: 10.5220/0002708201590164


in Bibtex Style

@conference{icaart10,
author={Mauricio Paletta and Pilar Herrero},
title={A MAS-BASED NEGOTIATION MECHANISM TO DEAL WITH SATURATED CONDITIONS IN DISTRIBUTED ENVIRONMENTS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2010},
pages={159-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002708201590164},
isbn={978-989-674-022-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - A MAS-BASED NEGOTIATION MECHANISM TO DEAL WITH SATURATED CONDITIONS IN DISTRIBUTED ENVIRONMENTS
SN - 978-989-674-022-1
AU - Paletta M.
AU - Herrero P.
PY - 2010
SP - 159
EP - 164
DO - 10.5220/0002708201590164