7th
Social Agents In A System Dynamics Environment
Since I read Social Atom by Mark Buchanan, I have been investigating agent-based models applied to economics and finance. Andrew Lo at MIT is working on behavioral finance models based on adaptive agents that evolve and are selected in a “survival of the fittest” environment. Rajiv Sethi refers to a Nature article applying agent-based models to macroeconomics.
What is interesting in agent-based models is that very simple rules at the individual agent level can create extremely complex system through interactions and networks of agents. Such networks would be able to model non-linear effects, by introducing stocks, flows and delays as suggested by System Dynamics theory.
That reminds me of a the Mandelbrot set fractals, where the iteration of an extremely simple equation generates an infinitely detailed image.
I think that a behavior rule for agents as simple as “do what the most successful agent did and avoid what failed/bankrupt agents did” would be enough to generate interesting results. As I develop my simple agent-based model, I will keep you posted with the results.
