Computational Approaches to Emotion in Artificial Psychology

Computational Approaches to Emotion in Artificial Psychology provides readers with a comprehensive introduction to how emotions can be processed by AI systems. It offers theoretical and practical guidance on data preprocessing and emotion analysis techniques, explores diverse real-world applications, and bridges the gap between AI and psychology.

Beginning with an introduction to the emerging field of artificial psychology, it explores the study, understanding, and recognition of emotions in various bodily signals, including facial expressions, voice, heart rate, and neural mechanisms. The book delves into data preprocessing for embodied emotion analysis, encompassing multiple data modalities like text, audio, visual, and gaze data, with a focus on Python basics for emotional AI. Additionally, it discusses EEG-based emotion decoding, emotional insights from medical imaging, affective image analysis, text-based emotion recognition, multimodal data integration, unsupervised learning for embodied emotion discovery, reinforcement learning, emotion elicitation, and predicting personality and emotional abilities using machine learning. The book concludes by examining the close relationship between cognition and emotion from the perspective of the universal structure of language and describing the use of deep fuzzy cognitive maps in diagnosing coronary artery disease.

By promoting research and innovation through case studies and experiments, it addresses the current lack of comprehensive resources in this interdisciplinary field, making it an essential reference for researchers, practitioners, students, and professionals seeking to navigate the intersection of AI and emotions.

Natasa Kovac is an associate professor at the Faculty of Applied Sciences, University of Donja Gorica. She defended her PhD thesis entitled "Metaheuristic approach to solving a class of optimization problems in transport" in 2018 at the Faculty of Mathematics, University of Belgrade, and at the same time acquired the title of Doctor of Mathematics. She was employed at the Faculty of Technical Sciences in Novi Sad and the Faculty of Maritime Studies in Kotor as an assistant. She worked as a lecturer at the Mediterranean University in Podgorica, and she also taught as a professor at the Gymnasium in Kotor. She is currently employed at the Faculty of Applied Sciences in Podgorica where she teaches euclidean and analytical geometry, stochastic processes and probability and mathematical statistics. Her research interests are statistical analysis, metaheuristics, optimization, algorithm development, and applied mathematics in engineering sciences. She has specializations in data science and was awarded the following certifications: Certified Data Collection and Processing with Python (University of Michigan), Statistics with Python specialization (University of Michigan), Introduction to Data Science specialization (IBM), Applied Data Science specialization (IBM), and IBM Data Science specialization (IBM). She has published more than 60 scientific papers and has been involved in more than 10 international projects. She is one of the founders of the SME "MoDrone" supported by the Montenegrin government, which is dedicated to the development and promotion of innovative solutions. She is a full member of the Scientific Research Honor Society Sigma Xi.

Hojjatollah Farahani is associate professor at the Tarbiat Modares University (TMU), Iran. He received his Ph.D. from Isfahan University in 2009, and he was a postdoctoral researcher in Fuzzy inference at the Victoria University in Australia (2014-2015), where he started working on Fuzzy Cognitive Maps (FCMs) under supervision of professor Yuan Miao. He is the author or co-author of more than 200 research papers and a reviewer in numerous scientific journals. He has supervised and advised many theses and dissertations in psychological sciences. His research interests and directions include psychometrics, advanced behavioral statistics, fuzzy psychology, artificial intelligence and machine learning algorithms in psychology. His recent book entitled “An Introduction to Artificial Psychology: Application Fuzzy Set Theory and Deep Machine Learning in Psychological Research using R” was published by Springer in 2023.

Peter Watson holds three degrees in Mathematical Statistics including a Ph.D. (Manchester). He has been providing statistical support in various ways to the research at CBSU, the Cognition and Brain Sciences Unit in Cambridge (and its predecessor, the Applied Psychology Unit) since 1994 (and prior to that fulfilling a similar role at the MRC Age and Cognitive Performance Research Centre in Manchester). He is the co-author of over 100 papers and lectures at the University of Cambridge. He is a statistical referee for several journals including BMJ Open and the Journal of Affective Disorders. He has also been a major contributor of articles to the on-line CBSU statswiki web pages which receive upwards of 100,000 visits annually. He has also been secretary, since 1996, of the Cambridge Statistics Discussion Group and chair and meetings organiser for the SPSS users’ group (ASSESS) since 2001 and has also been a member of the Clinical Trials Advisory Panel for Alzheimer’s Research UK.

Alessandro Grecucci is a prominent figure in the field of affective neuroscience and neurotechnology.
He holds a Ph.D. in 2010 and is currently an associate professor at the University of Bari, Italy. His
research focuses on the psychological and neural mechanisms of normal emotion generation and
regulation, as well as the development of biomarkers. Grecucci's work has been recognized with various awards and has been presented at international conferences, showcasing his significant contributions to the field.

Dionéia Motta Monte-Serrat is a distinguished researcher with a diverse academic background. Collaborating Researcher at the Department of Physics of the University of Sao Paulo, USP (2025- ), having previously collaborated with the Department of Computing and Mathematics at USP and the Language Institute of the University of Campinas, UNICAMP, Brazil. She holds a Direct Doctoral degree in Psychology from FFCLRP-USP, Brazil, and has completed a doctoral degree program partly at Université Paris III, Sorbonne Nouvelle. Her research interests span across various fields, including Neuroscience, Neurolinguistics, Brain Impairment, Artificial Intelligence, Neurophysiology, and Natural Language. She has contributed to the National Science Network for Education (Brazil), is a member of the British Wittgenstein Society, member of the Center for Artificial Intelligence, C4AI-USP-IBM-FAPESP, leader of a research group registered with the Ministry of Science and Technology, CNPq, Brazil, to promote best practices and evidence-based educational policies. Her work has been recognized with an ORCID iD and a ResearcherID, reflecting her significant contributions to the field of research.

Carlo Cattani is recognized as one of the top Italian scientists in the field of mathematics. His academic contributions span various subfields, including wavelets, fractals, fractional calculus, and nonlinear dynamics. Cattani has authored over 150 scientific articles and has co-authored multiple books. His research has been published in prestigious journals and has been recognized with an H-Index of 59 and 11,377 citations. He is affiliated with the University of Tuscia in Italy and has held various academic positions, including honorary professorships in Russia. Cattani's work has been influential in advancing the understanding of complex systems and has been recognized with numerous awards and honors.

Mirela C. C. Ramacciotti is a distinguished professional with a rich academic background and extensive experience in education, particularly in neuroscience, language acquisition, and pedagogical practices. She holds multiple advanced degrees, including two PhDs, and specializes in the transdisciplinary area of Mind, Brain, and Education. Her professional experience spans decades, and she is recognized for her contributions to the field through her research and publications. Ramacciotti is also involved in various educational initiatives and has been a consultant and trainer for schools in learning and education management. She is an Adjunct Coordinator for the National Science for Education Network (CpE Network) that promotes best practices and evidence-based educational policies.

Elpiniki Papageorgiou is a distinguished academic and researcher with a Ph.D. in Computer Science from the University of Patras. She has been involved in numerous research projects and has authored several publications in the field of artificial intelligence and decision support systems. Her work has been recognized with multiple citations and she has been involved in various European and Greek projects. Dr. Papageorgiou is also the Editor of the Springer book "Fuzzy Cognitive Maps for Applied Sciences and Engineering - from fundamentals to extensions and learning algorithms".