Recent advances in neurosciences and psychology have provided evidence that affective phenomena pervade intelligence at many levels, being inseparable from the cognitionaction loop. Perception, attention, memory, learning, decisionmaking, adaptation, communication and social interaction are some of the aspects influenced by them. This work draws its inspirations from neurobiology, psychophysics and sociology to approach the problem of building autonomous robots capable of interacting with each other and building strategies based on temperamental decision mechanism. Modelling emotions is a relatively recent focus in artificial intelligence and cognitive modelling. Such models can ideally inform our understanding of human behavior. We may see the development of computational models of emotion as a core research focus that will facilitate advances in the large array of computational systems that model, interpret or influence human behavior. We propose a model based on a scalable, flexible and modular approach to emotion which allows runtime evaluation between emotional quality and performance. The results achieved showed that the strategies based on temperamental decision mechanism strongly influence the system performance and there are evident dependency between emotional state of the agents and their temperamental type, as well as the dependency between the team performance and the temperamental configuration of the team members, and this enable us to conclude that the modular approach to emotional programming based on temperamental theory is the good choice to develop computational mind models for emotional behavioral Multi-Agent systems.
From Triggers to Emotions: A CPM-Grounded Appraisal Multi-Agent for Dynamic Emotional Evolution in Persona-Based Dialogue
National Centre for Computer Animation（国家计算机动画中心）；Information Hub（信息中心）；Key Laboratory of Child Cognition & Behavior Development of Hainan Province（海南省儿童认知与行为发展重点实验室）；Chief Technology Officer（首席技术官）；School of Health and Care（健康与护理学院）
Towards Efficient and Robust Linguistic Emotion Diagnosis for Mental Health via Multi-Agent Instruction Refinement
School of Computer Science and Technology, Xi’an Jiaotong University（计算机科学与技术学院，西安交通大学）；Saw Swee Hock School of Public Health, National University of Singapore（Saw Swee Hock 公共卫生学院，新加坡国立大学）
Agent-Based Modular Learning for Multimodal Emotion Recognition in Human-Agent Systems
Research Center of the Artificial Intelligence Institute, Innopolis University（人工智能研究所研究中心，因诺波利斯大学）；ITMO University（ITMO大学）；Saint Petersburg Electrotechnical University ``LETI''（圣彼得堡电工大学『LETI』）
How Emotion Shapes the Behavior of LLMs and Agents: A Mechanistic Study
School of Computer Science and Engineering, Beihang University（北京航空航天大学计算机科学与工程学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）
EvoEmo: Towards Evolved Emotional Policies for Adversarial LLM Agents in Multi-Turn Price Negotiation
Department of Engineering, University of Cambridge（剑桥大学工程系）；Rotman School of Management, University of Toronto（多伦多大学罗特曼管理学院）；TUM School of Management, Technical University of Munich（慕尼黑技术大学管理学院）；The Alan Turing Institute, London, UK（伦敦阿尔安·图灵研究院）
EmoAgent-R1: Towards Multimodal Emotion Understanding with Reinforcement Learning-based Dynamic Agent Specialization
Guangdong University of Technology（广东工业大学）；Southern University of Science and Technology（南方科技大学）；Xi’an Jiaotong University（西安交通大学）；Guizhou Provincial Laboratory of Big Data, State Key Laboratory of Public Big Data, Guizhou University（贵州大学大数据省级重点实验室、公共大数据国家重点实验室）
Steering Emotional Dynamics for Art Therapy: Controllable Narrative Script Generation through Hierarchically Guided LLM Agents
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）
Intelligent Agents with Emotional Intelligence: Current Trends, Challenges, and Future Prospects
School of Computer Engineering, Iran University of Science and Technology（伊朗科学技术大学计算机工程学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算机与数据科学学院）
Affective Multimodal Agents with Proactive Knowledge Grounding for Emotionally Aligned Marketing Dialogue
Hunan Police Academy, Department of Criminal Investigation（湖南警察学院犯罪侦查系）；Business College, California State University（加州州立大学长滩分校商学院）；Northwestern University（西北大学）；AI Agent Lab, Vokram Group（Vokram集团AI代理实验室）；Beijing University of Technology（北京理工大学）；Zheng Zhou University of Light Industry（郑州轻工业大学）
Building Altruistic and Moral AI Agent with Brain-inspired Emotional Empathy Mechanisms
Brain-inspired Cognitive AI Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, China（脑启发认知人工智能实验室，自动化研究所，中国科学院，北京，中国）；Beijing Key Laboratory of Safe AI and Superalignment, China（北京安全人工智能与超对齐关键实验室，中国）；Beijing Institute of AI Safety and Governance, China（北京人工智能安全与治理研究所，中国）；Long-term AI, Beijing, China（长期人工智能，北京，中国）；School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China（人工智能学院，中国科学院大学，北京，中国）；School of Humanities, University of Chinese Academy of Sciences, Beijing, China（人文学院，中国科学院大学，北京，中国）；State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, Shanghai, China（脑认知与脑启发智能技术国家重点实验室，中国科学院，上海，中国）
Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?
MBZUAI（穆罕默德·本·扎耶德人工智能大学）；Texas A&M University（德州农工大学）；National University of Singapore（新加坡国立大学）；UCLA（加州大学洛杉矶分校）；University of Texas at Austin（德克萨斯大学奥斯汀分校）；Mass General Hospital（麻省总医院）；Harvard Medical School（哈佛医学院）
