This paper describes a novel method for building affectively intelligent human-interactive agents. The method is based on a key sociological insight that has been developed and extensively verified over the last twenty years, but has yet to make an impact in artificial intelligence. The insight is that resource bounded humans will, by default, act to maintain affective consistency. Humans have culturally shared fundamental affective sentiments about identities, behaviours, and objects, and they act so that the transient affective sentiments created during interactions confirm the fundamental sentiments. Humans seek and create situations that confirm or are consistent with, and avoid and supress situations that disconfirm or are inconsistent with, their culturally shared affective sentiments. This "affect control principle" has been shown to be a powerful predictor of human behaviour. In this paper, we present a probabilistic and decision-theoretic generalisation of this principle, and we demonstrate how it can be leveraged to build affectively intelligent artificial agents. The new model, called BayesAct, can maintain multiple hypotheses about sentiments simultaneously as a probability distribution, and can make use of an explicit utility function to make value-directed action choices. This allows the model to generate affectively intelligent interactions with people by learning about their identity, predicting their behaviours using the affect control principle, and taking actions that are simultaneously goal-directed and affect-sensitive. We demonstrate this generalisation with a set of simulations. We then show how our model can be used as an emotional "plug-in" for artificially intelligent systems that interact with humans in two different settings: an exam practice assistant (tutor) and an assistive device for persons with a cognitive disability.
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）
Quantum Operation of Affective Artificial Intelligence
Bogolubov Laboratory of Theoretical Physics, Joint Institute for Nuclear Research（联合核研究所博戈柳博夫理论物理实验室）；Instituto de Fisica de São Carlos, Universidade de São Paulo（圣保罗大学圣卡洛斯物理研究所）
Soul Computing: A Theoretical Framework and Technical Architecture for Intelligent Agents with Independent Consciousness
Innovation and Management Center, School of Software Technology, Zhejiang University (Ningbo)（浙江大学（宁波）软件学院创新与管理中心）；School of Software Technology, Zhejiang University, Ningbo（浙江大学软件学院（宁波））
Applying a Text-Based Affective Dialogue System in Psychological Research: Case Studies on the Effects of System Behavior, Interaction Context and Social Exclusion
Blockchain-Enabled Routing for Zero-Trust Low-Altitude Intelligent Networks
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics（南京航空航天大学电子与信息学院）；College of Civil Aviation, Nanjing University of Aeronautics and Astronautics（南京航空航天大学民航学院）；College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics（南京航空航天大学人工智能学院）；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）
Towards Robust Deep Neural Networks for Affect and Depression Recognition from Speech
University of Paris-Est Créteil（巴黎东-克雷泰伊大学）；Sorbonne University（索邦大学）；INSAT（国立应用科学技术学院）；ENSIIE（国立工业环境高等工程师学院）；Polytechnic University of Hauts-de-France（上法兰西理工大学）
SensAI+Expanse Emotional Valence Prediction Studies with Cognition and Memory Integration
BioISI Faculdade de Ciências Universidade de Lisboa（里斯本大学生物信息学与系统生物学研究所 科学学院）；CICPSI Faculdade de Psicologia Universidade de Lisboa（里斯本大学心理学院心理研究与干预中心）
