Agent-Based Model and Machine Learning for the Analysis of Barter Regulated by Lotka-Volterra Equations in an Artificial Society

In this paper, agent-based modeling and random forest are used to model the exchange of goods and services through barter. It is regulated by the Lotka-Volterra equation system–which is often used to analyze the dynamics of populations of different species.

These equations, the ones that correspond to the case of mutualism between species, help to ensure that the amount of goods and services that a person can exchange does not accumulate during certain time among few individuals. This situation is repeated for the case in which empirical information is integrated into the modeling.

Through such information, the coincidence of desires is modeled with the help of the random forest technique, which allows the modeling to be more closely related to a real situation.