Economic Models Ignore Dependency and Irrationality - Is Agent Based Computing the Answer?

Summary

There is a nice article in the New Scientist Magazine (30th October 2010) by Philip Ball that looks at economic modelling.

It starts out by looking at the popular cause of the current economic crisis, the bankers and the American sub-prime mortgage market but points out the error in simply blaming the bankers , the opaque financial mechanisms and inducements to sell:

it ignores the complexities of a system that led the initially small perturbation of the "sub-prime" mortgage crisis to morph into systemic collapse. Moreover, concentrating on the specific causes of that one event fixates on the past at the expense of the future. When the next crisis comes, the disturbance will probably ripple out from another quarter of the economy, taking us completely unawares

It then asks if there is a better way in which we could prepare ourselves

Instead of making unrealistically simplistic assumptions about human behaviour and the properties of markets, we can harness the number-crunching power of modern computing, coupled with our emerging understanding of the physics of complex systems, to rebuild economic theory from the bottom up. Extending that approach to the social sciences more generally could help us develop forecasting tools to assess a whole range of problems threatening human society

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Visualisation of Relationships

Summary

This is a recurring theme. Systems-thinking, systems engineering and architecture description are primarily concerned with identifying and managing the important relationships with other things in the world. They are relationship-centric rather than object-centric.

It is often hard for folks used to using flat 2D diagrams produced in PowerPoint or Visio to appreciate the potential power behind relationships. Flat diagrams don't make it easy to explore nearby related things and because they're limited in terms of the parameters you can apply, for example weightings to indicate proximity or importance, you often need many versions or different cut-sets of the bigger one.

Having a means to store objects and relationships and represent them allows you to explore beyond the immediate vicinity to assess impacts and dependencies. There is a very nice example on TED.com of the use of relationships by ecologist Eric Berlow which is helped by the ability to visualise them in a nice way. This could be achieved using a architecture description repository although the visualisation is probably not as good. There are bound also to be other tools that are good at representing and filtering relationships - possibly harking back to the thoughts for visualisations of information sources using Resource Description Format (RDF). With Linked Data gaining ground you need only to be able to see that relationships or dependencies exist but to be able to see what affect the strength of that relationship has. The Mk1 Human Being is highly adapted to visual input and stimulus so it is perhaps not surprising that being able to see and manipulate visually is a powerful tool in identifying context and assessing impact.

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