The agent-based modeling paradigm has been actively applied to address social normative issues such as: values, cognition, morality and behaviors. The abstraction of human and human-like social processes and mechanisms result in misalignment of computational model with existing (old) verification and validation techniques and expose significant challenges. We argue that human sources represent a sound approach for verification and validation of agent-based social simulation models. We propose a novel conceptual gaming framework that extracts required information from relevant sources as part of game play.

Mental health has become an increasingly important topic to address as a surge in mental health issues can be seen across the globe significantly owing to the COVID-19 pandemic. Several factors such as unawareness, daily life interruptions, and social stigma lead to people hesitating in acquiring appropriate mental health support, thereby arising the need for effective and round-the-clock mental health support solutions. Hence, the purpose of this paper is to address how Artificial Intelligence (AI) in conjunction with the portability of smartphones, can be leveraged to provide a type of first aid for mental health to users in their moment of educational need. This article proposes a new mental health assistance solution in the form of a mobile application called Therapily. The ideation, design, and implementation aspects of this application will be explored along with discussing the technical details of the key modules to aid the education of the health domain. An emotion detection module employing a Deep Neural Network to analyze the user’s facial expressions for recognizing in-the-moment emotion(s) followed by suggesting therapeutic activities based on the results, will be explored. Moreover, the creation of a Natural Language Processing (NLP) - based chatbot and the functionality of online consultations with licensed and experienced therapists will also be covered. Finally, the different ways in which Therapily is likely to be extended or modified in the future will also be identified.

The understanding of the micro-macro link is an urgent need in the study of social systems. The complex adaptive nature of social systems adds to the challenges of understanding social interactions and system feedback and presents substantial scope and potential for extending the frontiers of computer-based research tools such as simulations and agent-based technologies. In this project, we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the development of collective social moral norms as representative sample of the bigger micro-macro link of social systems. We outline our computational model of ethical trust (CMET) informed by research findings from trust, machine ethics and neural science. Guided by the CMET architecture, we discuss key implementation ideas for the simulations of ethical trust and social moral norms.

Recent advances in the fields of robotics, cyborg development, moral psychology, trust, multi agent-based systems and socionics have raised the need for a better understanding of ethics, moral reasoning, judgment and decision-making within the system of man and machines. Here we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the social moral norms at the collective end. We review salient works in the fields of trust and machine ethics research, underscore the importance and the need for a deeper understanding of ethical trust at the individual level and the development of collective social moral norms. Drawing upon the recent findings from neural sciences on mirror-neuron system (MNS) and social cognition, we present a bio-inspired Computational Model of Ethical Trust (CMET) to allow investigations of the interplay of ethical trust and social moral norms.

In many agent-based models theoretical and computational mechanisms are needed for model abstraction and design. However, it can be challenging to arrive at the appropriate mechanisms and models. This research on the interplay of ethical trust and so