关键词: 协商模型, 半监督学习方法, 支持向量回归机, 偏好, 模拟退火算法

Abstract: Aiming at the automated negotiation problem, a co-training based semi-supervised opponent's negotiation preference learning method was proposed. In this method, negotiation process was mapped into two new feature spaces：price orbit feature space and interaction orbit feature space. Two support vector regression machines were trained in their feature space respectively, and confident labeled instances for each other alternately were provided, thus the scale of training samples was extended. The opponent's negotiation preference was obtained by two machines. Win-win negotiation counter proposal based on both sides'negotiation preference was proposed by negotiation decision model. Experiment results showed that the proposed method could improve total negotiation utility, reduce negotiation round and save negotiation time.

Key words: negotiation model, semi-supervised learning method, support vector regression machine, preference, simulated annealing algorithm