Developing a multi-issue and flexible negotiation mechanism based on multi-agent systems in the automated interchange

Document Type : Research Paper

Authors

1 Associate Prof. of industrial engineering department of Tarbiat Modares University of Tehran, Iran

2 PhD student of industrial engineering, Tarbiat Modares University of Tehran, Iran

Abstract

Agent-based negotiation is one of the interesting approaches in the field of automated negotiation in the E-Commerce world. Establishment an automated negotiation needs to develop a mechanism for it and it is obvious that users would accept a mechanism that is reliable alternative for negotiating individual. Therefore, the need to developing efficient and reliable agent-based negotiation mechanism is being felt. In this paper we present a multi-issue negotiation mechanism. In each round of this mechanism a twofold proposal is presented that caused the time of negotiation decreases while increasing the efficiency of negotiation and probability to reach better solutions. To do this, we focused on reasoning model of negotiation; First the decision making model of each agent about received offer is developed and then a novel method for generating counter offer is proposed. Validity and efficiency of proposed negotiation mechanism is indicated via predefined conditions of literature and a numerical example is solved.
 

Keywords

Main Subjects

References

Argoneto, P. & Renna, P. (2010). Production planning, negotiation and coalition integration: A new tool for an innovative e-business model. Robotics and Computer-Integrated Manufacturing, 26 (1):1–12.
Bajo, J., Corchado, J.M., De Paz, Y., De Paz, J.F., Rodríguez, S., Martín, Q. & Abraham, A. (2009). SHOMAS: Intelligent guidance and suggestions in shopping centres. Applied Soft Computing, 9 (2): 851–862.
Ballarini, P., Fisher, M. & Wooldridge, M.J. (2006). Automated Game Analysis via Probabilistic Model Checking: a case study. Electronic Notes in Theoretical Computer Science, 149 (2): 125–137.
Chavez, A., Maes, P. (1996). Kasbah: an agent marketplace for buying and selling goods. 1st International conference on the practical application of intelligent agents and Multiagent technology, London.
Costantino, F. & Gravio, G.D., (2009). Multistage bilateral bargaining model with incomplete information-A fuzzy approach.Int. J. Production Economics, 117 (2): 235–243.
Faratin, P., Sierra, C. & Jennings, N.R. (1998). Negotiation decision functions for autonomous agents. Robotics and Autonomous Systems, 24(3-4): 159-182.
Fischer, K., Muller, J.P., Heimig, I. & Scheer, A. (1996). Intelligent agents in virtual enterprises.1st International conference on the practical application of intelligent agents and Multiagent technology, London.
Haghighinasab, M. & Taghavy, S.S. (2012). Influencing factors in expanding e-business in Iranian organizations. Quarterly Journal of Information technology management, 4(10): 25-40. (in Persian)
Hajimiri, M.H., Ahmadabadi, M. & Rahimi-Kian, A. (2014). An intelligent negotiator agent design for bilateral contracts of electrical energy. Expert Systems with Applications, 41(9): 4073-4082.
Huns, M. and Singh, M. (1994). Multiagent Systems: A Theoretical Framework for Intentions, Know-How & Communications. Berlin: Heidelberg: Springer.
Jain, V. & Deshmukh, S.G. (2009). Dynamic supply chain modeling using a new fuzzy hybrid negotiation mechanism. International Journal of Production Economics, 122(1): 319-328.
Jiao, J., You, X. & Kumar, A. (2006).An agent-based framework for collaborative negotiation in the global manufacturing supply chain network. Robotics and Computer-Integrated Manufacturing, 22(3): 239-255.
Kebriaei, H. and Johari Majd, V. (2009). A simultaneous multi-attribute soft-bargaining design for bilateral contracts. Expert Systems with Applications, 36 (3): 4417-4422.
Kraus, S. (1997). Negotiation and cooperation in multi-agent environments. Artificial Intelligence, 94(1-2): 79-97.
Kraus, S. (2001). Strategic Negotiation in Multiagent Environments. UAS: MIT Press.
Lin, C.C., Chen, S.C. & Chu, Y.M. (2011). Automatic price negotiation on the web: an agent based web application using fuzzy expert systems. Expert Systems with Applications, 38(5): 5090-5100.
Matsomuto, K. (2008). Evaluation of an artificial market approach for GHG emissions trading analysis. Simulation Modeling Practice and Theory, 16(9): 1312–1322.
Moradi, M., Aghaei, A. & Hosseini, M. (2013). Applying Intelligent Multi-agent Systems in Decisions Making with Knowledge Management Approach.Quarterly Journal of Information technology management, 5(4): 219-244. (in Persian)
Muthoo, A. (1999). Bargaining Theory with Applications. UK: Cambridge University Press.
Nash, J.F. (1950). The Bargaining Problem. Econometrica, 18(2): 155-162.
Rao, A. & Georgeff, M. (1995). BDI Agents: From Theory to Practice, Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), San Francisco, USA.
Rubinstein, A. (1982).Perfect Equilibrium in a Bargaining Model. Econometrica, 50(1): 97-110.
Saunders, M., Lewis, Ph. & Thornhill, A. (2009).Research Methods for Business Students. USA: Prentice Hall.
Wang, G., Wong, T.N. & Yu, Ch. (2013).A computational model for multi-agent E-commerce negotiations with adaptive negotiation behaviors. Journal of Computational Science, 4(3): 135-143.
Weiss, G. (1999). Multiagent Systems: A Modern Approach to Distributed Modern Approach to Artificial Intelligence.USA: MIT Press.
Wooldridge, M. (2002). An Introduction to Multiagent Systems. UK: John Wiley & Sons, Ltd.
Journal of Information Technology Management
Volume 6, Issue 4 - Serial Number 4
February 2015
Pages 589-606

Files

Share

How to cite

Statistics