Background and Rationale

The subjects of complexity and agent-based modelling (ABM) are fast growing areas of research and theory in many sciences, including business and the social sciences generally. This interest is indicated perhaps most clearly with the award of the Nobel Prizes in Economics to Elinor Ostrom in 2009 for her work in complex systems and the management of common pool resources, to Thomas Schelling in 2005 for his work on the unintended macro outcomes of micro behaviour in complex systems, and to Vernon Smith in 2002 on the role of social relations and the self-organising properties of market systems (not to mention the very early one given to Herbert Simon).

Many types of socio-economic systems as well as psychological, biological and ecological systems are increasingly being understood as complex adaptive systems in which order emerges in a bottom-up self-organising manner from the micro interactions taking place over time among the actors comprising the system, be they chemicals, animals, humans or ideas. Such systems also interact with other systems which buffet and challenge them. There are also feedback effects in which large-scale order feeds back to affect local interactions. There is now a growing industry of pop and scientific books and articles describing complexity and what it means for understanding, researching and operating in complex adaptive systems of different kinds. For more information and resources concerning complexity and agent-based modelling, visit the Agent-Based Computational Economics (ACE) site run by Professor Leigh Tesfatsion. The site covers material and resources related to learning and teaching, research and demonstration programs in a wide variety of disciplines, not just economics.

Simulation using agent-based modelling methods plays an essential role in the study of complex adaptive systems. This is because highly non-linear systems of this kind, though they can in principle be written down in mathematical form, are beyond traditional methods of solution. The only option is to compute the results of the rules over time using computers, hence the use of terms such as computational economics and computational social science. Agent-based models of business and social systems offer a way forward in studying the behaviour and evolution of complex systems that would not be possible otherwise. Such models are not the same as previous types of simulations such as Monte Carlo methods or System Dynamics. The models construct complex systems from the bottom up by specifying the individual agents? characteristics and values, how they change and interact with other agents, and the environmental agents and conditions in which they operate.

Not only is it impossible to solve the highly nonlinear mathematical equations of motion of such systems with all the interactions taking place, it is also not physically, economically or morally possible to conduct the range experiments required to tease out the effects of different elements of such business and social systems. Once again we are led back to simulation and agent-based models that are now possible given rapid improvements in the power and accessibility of computers and developments in object-oriented programming methods.

A major factor limiting serious science and agent-based modelling of complex adaptive systems in marketing, business and the social sciences is a lack of adequate programming skills among researchers, who are generally not trained in such techniques, which are not easy to acquire. Or, rather, this was the case until quite recently, but as a result of developments in more user-friendly, agent-based modelling systems and programming languages researchers can more readily learn these techniques. The trouble is there are limited opportunities for them to do so. This intensive course is designed to provide a solution to this problem for researchers in our region. We plan to repeat it on a regular basis. There are few courses of this type offered anywhere in the world and none has so far been offered in Australia. David Earnest is one of the few academics willing and able to offer such a course.