Wu Jinghua, Cao Ruiyang, Zhang Ya, Li Yan
School of management, China University of Mining and Technology - Beijing, Beijing, China.
PLoS One. 2025 Sep 25;20(9):e0333078. doi: 10.1371/journal.pone.0333078. eCollection 2025.
Automated negotiation agents require human-like adaptability in emotionally charged and time-constrained settings. This study introduces an Emotion-Time Dual-Process Framework that integrates the Appraisal Tendency Framework with dynamic temporal modeling. Emotions are decomposed into pleasantness and certainty dimensions and mapped to six emotional persuasion strategies. A variable-rate time function is designed to capture the perceptions of dynamic time pressure. Emotion and time pressure jointly drive a state-dependent concession updating model. The proposed framework was validated through a series of simulation experiments based on different scenarios. The results demonstrate that the proposed framework has significant advantages in improving negotiation success rates, joint utility, and outcome fairness against baseline models. In particular, incorporating emotional factors reduces utility disparity between parties by 28.55%, while the proposed time function improves negotiation efficiency by 12.99% without sacrificing fairness or the success rate. This study provides a theorical basis for developing highly more human-like and adaptive intelligent negotiation systems.
自动化谈判代理在充满情感且时间紧迫的环境中需要具备类似人类的适应性。本研究引入了一个情感-时间双过程框架，该框架将评估倾向框架与动态时间建模相结合。情感被分解为愉悦度和确定度维度，并映射到六种情感说服策略。设计了一个可变速率时间函数来捕捉对动态时间压力的感知。情感和时间压力共同驱动一个状态依赖的让步更新模型。通过基于不同场景的一系列模拟实验对所提出的框架进行了验证。结果表明，与基线模型相比，所提出的框架在提高谈判成功率、联合效用和结果公平性方面具有显著优势。特别是，纳入情感因素可使各方之间的效用差距降低28.55%，而所提出的时间函数在不牺牲公平性或成功率的情况下将谈判效率提高了12.99%。本研究为开发更具人类特征和适应性的智能谈判系统提供了理论基础。
