The core focus of the biologically inspired artificial intelligence research group within is to devise new methods using techniques from a broad range of biologically inspired artificial intelligence sub-fields such as evolutionary computation and artificial neural networks (neuro-evolution) as well as statistical machine learning and apply such methods to evolve and adapt artificial brains on various experimental platforms including: Evolutionary Robotics, Artificial Life and Agent-Based Systems. Within the broad purview of artificial intelligence, the guiding research goal is to use adaptive artificial systems in order elucidate open how and why questions in the evolution and adaptive behaviour of counter-part natural systems as well as to apply novel adaptive algorithms to the synthesis of problem-solving computational tools and the engineering of robotic systems.

    Current Research Projects


  • Project Title : The Emergence of Social Complexity and an Autocratic State in Predynastic Egypt: An Agent-Based Approach
  • Funding : National Research Foundation : Human and Social Dynamics in Development (2019 - 2021) : Grant No: 118557.
  • Collaborators : Dr. J Nitschke, Department of Ancient Studies, Stellenbosch University.
  • Bursaries : For MSc and PhD students and a post-doctoral researcher are currently available for 2020-2021. Contact Geoff Nitschke for details.
  • Abstract : The origin and rise of complex states in antiquity has been a subject of considerable debate since the beginning of the modern discipline of archaeology. The case of ancient Egypt, one of the world's earliest and longest-lived examples of a pristine state, has long been a point of fascination for scholars, but without a clear consensus on how or why this state emerged when and where it did. Although there has been considerable advances in archaeological research in Predynastic Egypt in the past several decades, scholars still struggle to adequately narrate and understand this process. This is partially because of the fragmentary nature of the archaeological record, but also because of an inability to test and critically evaluate narrative models. What is needed are better analytical tools for developing, testing, challenging, and consequently improving our narrative models and reconstructions.

    This project proposes to develop such a tool in the form of an Agent-Based Model (ABM), a type of computational simulation long favoured in the social sciences for its ability to study and analyse complex system behaviour, The model will be used to design experiments that examine the social dynamics of early Egypt, including the emergence of entrenched inequality, urbanism, social hierarchy, networks, and ideology of kingship. The goal is to demonstrate how the Egyptian state emerged as a result of the meaningful actions of individuals pursuing their own interests within the particular environmental conditions of the Nile Valley in the fourth millennium BC, as well as compare this system to similar case studies in social complexity in Africa more broadly.