The International Arab Journal of Information Technology (IAJIT)

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Bilateral Multi-Issue Negotiation Model for a Kind

There are many uncertain factors in bilateral multi-issue negotiation in complex environments, such as unknown opponents and time constraints. The key of negotiation in complex environment is the negotiation strategy of Agent. We use Gaussian process regression and dynamic risk strategies to predict the opponent concessions, and according to the utility of the opponent’s offer and the risk function, predict the concessions of opponent, then set the concessions rate of our Agent upon the opponent's concession strategy. We run the Agent in Generic Environment for Negotiation with Intelligent multi-purpose Usage Simulation (GENIUS) platform and analyze the results of experiments. Experimental results show that the application of dynamic risk strategy in negotiation model is superior to other risk strategies.


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[18] Yu C., Ji G., Hua-Mao G., and Zhao-Yang F., Automated Negotiation Decision Model Based on Machine Learning, Journal of Software, vol. 20, no. 8, pp. 2160-2169, 2009. Jun Hu born in 1971 and received M.Sc. in Computer Application from Kunming University of Science and Technology, Kunming, China, and Ph.D. in Computer Science and Technology from Zhejiang University, Hangzhou, China. In 2010, he was an academic visitor at University of Southampton working on multi-agent system. Currently, he is an associate professor of Hunan University, Changsha, China. Senior member of China Computer Federation (CCF). His research interests include multi-agent system, distributed artificial intelligence and software engineering. Li Zou, born in 1988. He gets the M.A's degrees in computer science and technology from Hunan University, Changsha, China, 2014. His main research interests include automated negotiation and multi agent system. Ru Xu, born in 1990. She gets the M.A's degrees in computer technology from Hunan University, Changsha, China, 2015. Her main research interests include artificial intelligence and multi-agent system.