基于合同网的虚拟企业多智能体协商研究

协商是虚拟企业成员之间协作的一种实现方式。通过深入分析多智能体的协商框架、协商模型和协商过程等，在合同网协议的基础上，构建多智能体协商体系框架，并结合贝叶斯决策方法，来建立自学习协商模型。根据协商中的更新信息，实时更新智能体信念，实现多智能体协商过程的自学习功能。从而有利于提高协商效率，改善网络通信，保证虚拟企业的敏捷性和协商双方的利益。

Multi-agent Learning Negotiation Research in Virtual Enterprise Based on Contract Net

With the demand of modern global market competence, the negotiation has been used as a mechanism to solve the task distribution, coordination and conflict in virtual enterprises. The contract net protocol tends to bring communication congestion when used in negotiation. In this paper, the Bayesian decision making is introduced to extend the contract net protocol, and a multi-agent negotiation system architecture is constructed. Agents with incomplete information about their opponent can update their belief when taking into consideration what other agents are thinking about during their interactions. The initial experimental results are given and it is proved that the learning model reduces the information exchange times between agents and increases their utility.