This project aims to investigate a bio-inspired approach to developing computer systems. By studying social insect based models we hope to gain a new understanding of complex systems and how the seemingly intelligent behaviors of the assemblage arise from the behavior of the individual agents, leading to innovative solutions to complex tasks. Here we present the 3D simulation of the emergent behaviour of Macrotermitinae termites. Similar processes can be seen in many other complex systems. For example: a termite colony can be contrasted with cells in an organism, communicating via various quantitative communication media: morphogens, electric signals and hormone gradients. This use of reaction-diffusion, stochasticity, dynamic self-organisation and adaptive behaviour are all recurring aspects of complex systems that self-organise to form global patterns in a given environment.

The top-down approach models the global behavior directly without considering the local interaction that contributes to this global behavior. For example, some use Partial Differential Equations (PDEs) to model termites. Equations are easy to simulate and evaluate. However, they suffer from many disadvantages. They are difficult to describe as the model become more complex. They are difficult to modify to incorporate more complex interactions. These models are also often deterministic - the specified parameters are used each time the simulation is run, so the same results will occur. A better approach is to model a topology within which interaction may occur and at each location in that topology how the contents may change based on its current state, neighboring states and possibly global effects.

Agent-based simulation model individuals within their topology and their behavior, e.g., how they interact with their model. The key aspect of the simulation is that the larger simulation has been broken into a number of smaller components. This often makes it easy to modify the simulation in order to examine different scenarios.

A representative Macrotermes mound can be 3 to 4 meters high and is essentially made from selected, graded and bonded soil pellets. Inside, the mound is dominated by passages and ducts, which surround the nest and perform air-conditioning functions. Within these fully enclosed and protective architectures, survival of such large populations of termites is dominated by the requirement to stabilise the mound’s temperature, moisture levels and respiratory gas balance. Solutions to the problem are impressive and are analogous to the function of the animal lung and thermo-regulatory systems which, in the case of Macrotermes mounds, is driven by the activity of the termites within. In fact, in physiological terms, the termites have evolved to outsource many of the homeostatic functions (including the digestive function which is performed within fungus gardens surrounding the nest) into the mound structure itself. The ‘outsourcing’ of biological function results in a net energy gain within the colony, which drives the activity of the termites to maintain and modify the dynamic adaptations exhibited by the mound structure which is referred to as social homeostasis. Of key importance to this research is how Macrotermes produce such complex architectures, from their combined actions, without any obvious global control mechanism. The system operates on a remarkable ‘indirect’ communication mechanism where workers respond and adapt to constantly changing internal conditions and external influences to maintain equilibrium within the mound. The study of emergent behaviours, displayed by social insect, is termed Swarm Intelligence.