Complex adaptive systems: Using a free-market simulation to estimate attribute relevance

Abstract

The authors have implemented a complex adaptive simulation of an agent-based exchange to estimate the relative importance of attributes in a data set. This simulation uses an individual, transaction-based voting mechanism to help the system estimate the importance of each variable at the system/aggregate level. Two variations of information gain - one using entropy and one using similarity - were used to demonstrate that the resulting estimates can be computed using a smaller subset of the data and greater accommodation for missing and erroneous data than traditional methods. © Springer-Verlag Berlin Heidelberg 2006.