Background Complex Adaptive Systems involve a large number of variables. These variables are essentially inputs from complex processes which can often be modeled as agents. The data generated from these systems can be considerably nonlinear and difficult to understand.
Problem Statement In systems which are very closely linked to the human world, often times, there is a need to make quick or at least, expensive decisions in a relatively shorter amount of time.
Research Outcome The presented research reaffirms the belief of the Complex Adaptive Systems (CAS) community that simpler models can be considerably better in terms of making decisions.