Evolutionary Economic Agents

Abstract

An empirical work is described which compares the optimization levels produced by a group of economic agents versus those of a similar group of economic agents which additionally employ a genetic algorithm (GA) to attain a higher level of optimization. The problem domain is multimodal. It incorporates multiple hard and soft constraints and dynamical behaviors. It also has areas of infeasibility and non-linear behaviors. The simulated model environment provides several types of sensors, actuators and opportunities for interagent resource mediation. Evidence is offered to support the theory that multiple weak methods operating in concert, on a shared problem, can produce better results than the individual weak methods acting alone. The problem area is resistant to the use of strong methods.