基于信任度的协同商务链自学习协商研究

在传统合同网协议的基础上，构建了协同商务链自学习协商框架．借鉴群体智能技术中的响应阀值概念，提出了基于信任度的自学习协商模型，同时给出实现该模型的算法和步骤．根据协商过程中投标主体完成任务的情况，实时更新其信任度值．基于此动态值，管理者可以有效的选择合适的投标主体，提高了协商效率，并减少协商时间和成本，从而达到减少通信量和保证协同商务链上各主体利益的目的．最后，通过仿真实验，从通信量、时间和任务完成数3个指标来进行比较．结果表明：该模型可以有效缓解协商过程中的管理器瓶颈和信息拥塞问题，相对于单任务双方协商模型，其在解决多主体、任务不断变动的动态环境下的协商问题有明显的优势．

Negotiation Research on Collaborative Commerce Chain Based on Trust

Based on traditional contract net protocol, the self-study negotiation framework of collaborative commerce chain was described. Refering to response threshold model in multi-agents, the self-study negotiation model based on trust and the maneuverability steps to perform the model was investigated. In the process of negotiation, the trust degree of bidders was corrected in real time according to the situation of their accomplish tasks. On the basis of the dynamic trust degree, the manager can informing and selecting the suitable bidders directly and availably. The negotiation time and cost were reduced, and the benefits of all collaborative enterprises were protected. Finally, an experiment was introduced to illustrate the previous model. The results show that the model can ease up the bottleneck of management processor and communication congestion produced in negotiation efficaciously. And it has the obvious advantages in solving the negotiation problems under the condition of multi-bidders and fluctuant tasks.