An agent-based persuasion model using emotion-driven concession and multi-objective optimization

• Published in: Autonomous agents and multi-agent systems Vol. 38; no. 2
• Main Authors: Wang, Zhenwu, Shen, Jiayin, Tang, Xiaosong, Han, Mengjie, Feng, Zhenhua, Wu, Jinghua
• Format: Journal Article
• Language: English
• Published: New York Springer US 2024; Springer Nature B.V
• Subjects: Anthropomorphism; Artificial Intelligence; Computer Science; Computer Systems Organization and Communication Networks; Emotions; Multiple objective analysis; Negotiations; Optimization; Parameter sensitivity; Sensitivity enhancement; Software Engineering/Programming and Operating Systems; User Interfaces and Human Computer Interaction; Concession strategy; Multi-objective optimization; Agent-based emotional persuasion; Persuasion behavior; Multi-attribute negotiation
• ISSN: 1387-2532; 1573-7454; 1573-7454
• DOI: 10.1007/s10458-024-09664-7

Multi-attribute negotiation is essentially a multi-objective optimization (MOO) problem, where models of agent-based emotional persuasion (EP) can exhibit characteristics of anthropomorphism. This paper proposes a novel EP model by fusing the strategy of emotion-driven concession with the method of multi-objective optimization (EDC-MOO). Firstly, a comprehensive emotion model is designed to enhance the authenticity of the emotion. A novel concession strategy is then proposed to enable the concession to be dynamically tuned by the emotions of the agents. Finally, a new EP model is constructed by integrating emotion, historical transaction, persuasion behavior, and concession strategy under the framework of MOO. Comprehensive experiments on bilateral negotiation are conducted to illustrate and validate the effectiveness of EDC-MOO. These include an analysis of negotiations under five distinct persuasion styles, a comparison of EDC-MOO with a non-emotion-based MOO negotiation model and classic trade-off strategies, negotiations between emotion-driven and non-emotion-driven agents, and negotiations involving human participants. A detailed analysis of parameter sensitivity is also discussed. Experimental results show that the proposed EDC-MOO model can enhance the diversity of the negotiation process and the anthropomorphism of the bilateral agents, thereby improving the social welfare of both parties.