Title :
Research on Multi-Agent Automatic Negotiation Based on Machine Learning
Author :
Hua, Jiang ; Jing, Yang
Author_Institution :
Sch. of Econ. & Manage., Hebei Univ. of Eng., Handan, China
Abstract :
At present, applying machine learning theory to the multi-agent automatic negotiation system has become the latest research focus in e-commerce area. The paper aimed at using Bayesian rules to update the environmental information in negotiation, using the Q-learning algorithm of reinforcement-learning to generate the negotiation proposals, and established a multi-agent automatic negotiation model based on machine learning, and expanded the traditional Q-learning algorithm, and designed the dynamic Q-learning algorithm based on the current belief and the recent exploring surplus. Furthermore, the convergence of the algorithm has been verified by experiments.
Keywords :
Bayes methods; learning (artificial intelligence); multi-agent systems; Bayesian rule; dynamic Q-learning algorithm; e-commerce; machine learning theory; multiagent automatic negotiation model; reinforcement learning; Bayesian methods; Environmental economics; Information technology; Learning systems; Machine learning; Machine learning algorithms; Multiagent systems; Proposals; Protocols; Technology management; Machine Learning; Multi-Agent Automatic Negotiation;
Conference_Titel :
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3497-8
DOI :
10.1109/IITA.2008.153