An agent-based emotional persuasion model driven by integrated trust assessment

Recent research on automated negotiation has primarily focused on improving the artificial intelligence of agents and equipping them with more flexible internal mechanisms to facilitate high-quality negotiations. However, the study on the systematic modeling of human-like psychological and behavioral activities and their role in the negotiation process is still in its early stages. In light of this, this paper proposes an emotional persuasion model that takes into account the effect of negotiators' integrated trust assessments on negotiation. Firstly, the paper presents a negotiation agent with both cognitive and emotional functions, detailing its internal system and operating mechanism. Secondly, the integrated trust of a negotiator is obtained by evaluating multiple single trusts, and the mapping of the integrated trust to the negotiation round parameter is modeled. Integrated trust is also parameterized into the agent's cognitive processes. Finally, the paper introduces a new framework for the generation of emotional persuasive behavior to assist agents in making new proposals. A series of experiments were conducted, yielding the following results: Compared with the non-emotional model, the performance of negotiation rounds and utility differences improved by 7.97 % and 4.81 %, respectively. Furthermore, the trust- driven emotional persuasion model outperformed the several existing competing models by at least 31.1 % in utility difference and 81.0 % in negotiation rounds. Additionally, a case study of human-computer negotiation demonstrated that the agent designed using the proposed method has negotiating capabilities comparable to those of a real human, which further showcases the application effect of the artificial intelligence agent in practice.