The Use of Hybrid Agent Based Systems to Model Petrol Markets

Summary

The petrol price market is a highly sensitive and competitive market with many processes combining at different temporal and spatial scales to affect each petrol station’s prices. Previous models developed to represent the relationship between petrol and a variable are empirical and mathematical. These suffer from a number of problems, chiefly: the parameters are all on the same scale (behaviours executed at the ‘micro’ level are not tied to ‘global’ level variables like oil prices); the parameters are often difficult to estimate and lack realism; very little, if any, account of any geographical effects is taken, and, finally, mathematical models by their nature only consider quantitative parameters and therefore miss out on qualitative, behavioural information.

The work within this paper presents a series of three multi-agent and hybrid models that seek to rectify some of these problems. The models are behavioural and work at the scale of the individual. The results show that this is a promising method for modelling dynamic, geographical systems.