Lo Jia-Hsun, Huang Han-Pang, Lo Jie-Shih
Department of Mechanical Engineering, National Taiwan University, Taipei, Taiwan.
Department of Health Psychology, Chang Jung Christian University, Tainan, Taiwan.
Sci Rep. 2025 May 16;15(1):16993. doi: 10.1038/s41598-025-01528-8.
The inherence of personality in human-robot interaction enhances conversational dynamics and user experience. The deployment of Chat GPT-4 within a cognitive robot framework is designed by using state-space realization to emulate specific personality traits, incorporating elements of emotion, motivation, visual attention, and both short-term and long-term memory. The encoding and retrieval of long-term memory are facilitated through document embedding techniques, while emotions are generated based on predictions of future events. This framework processes textual and visual information, responding or initiating actions in accordance with the configured personality settings and cognitive processes. The constancy and effectiveness of the personality simulation have been compared to human baseline and validated via two personality assessments: the International Personality Item Pool - Neuroticism, Extraversion and Openness (IPIP-NEO) and the Big Five personality test. Our proposed personality model of cognitive robot is designed by using Kelly's role construct repertory, Cattell's 16 personality factors and preferences, which are analyzed by construct validity and compared to human subjects. Theory of mind is observed in personality simulation, which perform better second-order of belief compared to other agent on the improved theory of mind dataset (ToMi dataset). Based on the proposed methods, our designed robot, Mobi, is enable to chat based on its own personality, handle social conflicts and understand user's intent. Such simulations can achieve a high degree of human likeness, characterized by conversations that are flexible and imbued with intention.
在人机交互中，个性的内在性增强了对话动态性和用户体验。在认知机器人框架中部署Chat GPT-4的设计方法是利用状态空间实现来模拟特定的个性特征，融入情感、动机、视觉注意力以及短期和长期记忆等元素。长期记忆的编码和检索通过文档嵌入技术实现，而情感则基于对未来事件的预测生成。该框架处理文本和视觉信息，根据配置的个性设置和认知过程做出响应或发起行动。个性模拟的稳定性和有效性已与人类基线进行比较，并通过两项个性评估进行验证：国际个性项目池 - 神经质、外向性和开放性（IPIP-NEO）以及大五人格测试。我们提出的认知机器人个性模型是利用凯利的角色构念 repertory、卡特尔的16种个性因素和偏好设计的，通过结构效度进行分析并与人类受试者进行比较。在个性模拟中观察到心理理论，在改进的心理理论数据集（ToMi数据集）上，与其他智能体相比，它在二阶信念方面表现更好。基于所提出的方法，我们设计的机器人Mobi能够基于自身个性进行聊天、处理社会冲突并理解用户意图。这种模拟可以实现高度的拟人化，其特点是对话灵活且充满意图。
