Dr. Simon Powers is a Lecturer at the School of Computing Engineering and the Built Environment at Edinburgh Napier University, where he is affiliated with the Centre for Algorithms, Visualisation and Evolving Systems (CAVES). His research focuses on agent-based modeling, evolutionary game theory, and the application of these techniques to understand social behavior, traffic systems, and human-AI interactions. Dr. Powers' research interests span multiple interdisciplinary domains: Agent-based modeling and simulation of complex systems Evolutionary game theory applications to social behavior Trust dynamics in human-AI interactions Leadership and consensus decision-making in social organisms Reciprocity mechanisms across human societies Traffic simulation and individual travel behavior modeling Dr. Powers' publication record demonstrates consistent contributions to agent-based modeling, with recent work focusing on trust in AI systems, leadership dynamics, and traffic simulation. His research shows a strong interdisciplinary approach, bridging computer science, social sciences, and evolutionary theory. The articles reveal a pattern of increasingly sophisticated modeling techniques applied to complex social phenomena, with particular attention to how individual behaviors aggregate to produce emergent systemic properties. Notable scientific contributions and recognitions include: Appointment as Associate Editor for the journal Adaptive Behavior (2017) Keynote speaker at the Second International Workshop of Social Learning and Cultural Evolution (2017) Invitation to contribute to the Encyclopedia of Evolutionary Psychological Science (2016) Dr. Powers has supervised several PhD students, including Johannes Nguyen (2020-2024) and Cedric Perret (2016-2020), and has collaborated extensively with researchers in the Centre for Algorithms, Visualisation and Evolving Systems. His work often involves developing novel modeling frameworks and notations, such as the Multi-Agent Modelling Notation (MAMN), to better understand complex adaptive systems. His research has practical applications in traffic management, AI governance, and understanding social dynamics, with recent work examining how regulation alone cannot ensure justifiable trust in AI systems.








