We describe an agent-based simulation of a fictional (but feasible)information trading business. The Gas Price Information Trader (GPIT) buysinformation about real-time gas prices in a metropolitan area from drivers andresells the information to drivers who need to refuel their vehicles. Our simulation uses real world geographic data, lifestyle-dependent drivingpatterns and vehicle models to create an agent-based model of the drivers. Weuse real world statistics of gas price fluctuation to create scenarios oftemporal and spatial distribution of gas prices. The price of the informationis determined on a case-by-case basis through a simple negotiation model. Thetrader and the customers are adapting their negotiation strategies based ontheir historical profits. We are interested in the general properties of the emerging informationmarket: the amount of realizable profit and its distribution between the traderand customers, the business strategies necessary to keep the market operational(such as promotional deals), the price elasticity of demand and the impact ofpricing strategies on the profit.
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