ABM General

Traditional Applications of ABM

Broad uses

Traditionally used on the macro level, ABM has been applied in areas such as social science, networking and behaviour, logistics, ecology and economics, to name a few. It is particularly powerful in modelling and predicting emergent properties of systems made up of many individual agents. Examples range from traffic congestion to flocking in fish. Swarm intelligence and emergence are fascinating concepts with implications in applications from protein structure to termite nests, all of which can exploit ABM. Modelling in these fields has been often limited to our imagination or oversimplified environments, but can now be realised accurately and graphically. 2D cellular automation simulations can be extended to massive multidimensional environments with complex interaction between entities. Micro and molecular biology which can encompass quantum physics to biochemistry to cellular interactions is arguably more complex and a lot less easy to visualise and manipulate than say traffic systems, which consist of roads and vehicles. The potential in systems biology for ABM is the reason why it is rapidly emerging as a new principal field.


Illinois electric power market elements, showing generating companies and ownership relationships (left), electric generators and transmission network (centre), and service area loads (right). (http://www.scidacreview.org/0802/html/abms.html)

Similar fields

On the macro level of biology there are some more emerging applications which hold similar potential and complexity in addition to the traditional ecology based uses, often concerning group behaviour. These can involve encompassing principles such as evolution and earth science with existing ecological models, in an attempt to answer the more fundamental questions. As Hywel Williams, a leading researcher in the field, puts it, understanding 'the co evolution of life and its physical environment'. Now we understand the broad fundamentals of evolution, we need to go about understanding the detail, so much so as to actually enable us to predict and model it in specific species. Hywel's work attempts to go so far as to predict the evolution of not only individuals in a certain environment, but also their emergent behaviour, which is undoubtedly equally derived. He aims to 'explore the evolutionary emergence of environmental regulation' using ABM's of microbial evolutionary ecology. To read more about his work, click here.