Coupled computational simulation and empirical research into the foraging system of Pharaoh's ant (Monomorium pharaonis).

The Pharaoh's ant (Monomorium pharaonis), a significant pest in many human environments, is phenomenally successful at locating and exploiting available food resources. Several pheromones are utilized in the self-organized foraging of this ant but most aspects of the overall system are poorly characterised. Agent-based modelling of ants as individual complex X-machines facilitates study of the mechanisms underlying the emergence of trails and aids understanding of the process. Conducting simultaneous modelling, and simulation, alongside empirical biological studies is shown to drive the research by formulating hypotheses that must be tested before the model can be verified and extended. Integration of newly characterised behavioural processes into the overall model will enable testing of general theories giving insight into division of labour within insect societies. This study aims to establish a new paradigm in computational modelling applicable to all types of multi-agent biological systems, from tissues to animal societies, as a powerful tool to accelerate basic research.