基于人工免疫算法的多属性谈判模型

在基于多Agent的多属性谈判过程中，谈判Agent间常因追求自身最大利益导致谈判陷入僵局。为此，将谈判目标视为抗原，将候选提议视为抗体，建立基于人工免疫算法的多属性谈判模型。该模型通过抗原与抗体的免疫过程，取得谈判双方整体利益的最大化。仿真实验表明，该模型可有效解决谈判僵局问题，提高谈判的适应性及效率。

Multi-attribute Negotiation Model Based on Artificial Immune Algorithm

In the process of multi-attributes automated negotiation based on multi-Agent,because the negotiation Agents pursue their respective interest,the negotiation is sometimes at a stand.This paper proposes a multi-attributes negotiation model based on artificial immune algorithm for solving above question.The model uses the artificial immune algorithm and considers the negotiation goal as antigen and considers the candidate proposal as antibody.By the immune process of antigen and antibody,the model enables the Agents to achieve a win-win trading program.Simulation experiment proves the validity and usefulness of this model.This paper provides a new approach for finding the optimal negotiation solution.It solves the impasse during the process of negotiation and improves the efficiency and adaptability of negotiation.