Bilateral Trading Simulator

The above is a screenshot of the simulation landscape that I used for my thesis on bilateral tradings in a mobile environment. It was modeled after the Sugarscape model that was used by Joshua Epstein and Robert Axtell in their research on artificial societies. Their findings was published in the book "Growing Artificial Societies: Social Science From the Bottom Up".

As part of my final year requirements, I was required to write a thesis. My professor had originally intended for me to use my programming skills to help him develop a tool for multi-agent simulations based on what he read about Sugarscape. Using Java (which I picked up while writing this tool), I developed the Bilateral Trading Simulator, in which mobile agents move around in a landscape, harvesting resources and trading those resources.

Price is determined in one of four ways. It can be a global price, which is the average price that each agent is willing to pay for each resource. Or it can be a local price, which is the price each agent is willing to barter at with the agent that it is trading with. Or it can be a game of bargaining, in which each agent either tries to get a price most beneficial to itself, or succumbs to the demands of its trading partner. The last way to determine price is a global price that is determined using a logistics function.

I finished the simulator in 3 months, when I had 10 months to do my thesis, so I managed to persuade my professor to allow me to carry out simulations using the simulator and analysing the results. One of the findings is that when individuals exercise their bargaining power to influence the price of bilateral tradings, the artificial society as a whole becomes more efficient. I guess that gives us a reason to be selfish.

The simulator was also modified by a fellow student for his research in simulation of the immune system.