A candidate framework for integration of theoretical, modeling and experimental approaches to understanding emotional intelligence is described. The framework includes three elements of a new kind that enable representation of emotional cognition: an emotional state, an appraisal, and a moral schema. These elements are integrated with the weak semantic cognitive map representing the values of emotional appraisals. The framework is tested on interpretation of results obtained in two new experimental paradigms that reveal general features of human emotional cognition, such as the emergence of subjectively perceived persistent roles of individual virtual actors.

Artificial intelligence (AI) is growing in diversity of application and influence. From healthcare, education, business management, sports to space exploration; the role of AI is expanding rapidly. The current AI applications are predominantly data-driven running algorithms designed by humans. The Deep Learning (DL) / Machine Learning (ML) based AI technologies process large amounts of data and learn from the data to provide improved predictions and inferences, which are revolutionizing working and operations across a wide array of business functions. At the same time, despite being termed artificial intelligence, the current AI applications lack genuine intelligence per se.