A Bacterial Foraging Framework for Agent Based Modeling

Abstract

Swarm optimization algorithms and agent based modeling (ABM) are two closely related research areas, parts of the multi agent system field, but they are traditionally not combined. Swarm optimization, in this case the bacterial foraging optimization (BFO), searches for an optimal solution while the ABM searches for a conclusion which resembles the real world, and it can be far from optimal. To bridge the gap, the overall goal this paper is to propose a new paradigm in the form of an architecture and operation procedures, thus creating a BFO-ABM hybrid. The other goal is to create a method which enables 3D visualization of the BFO algorithm. Firstly, an environment is created together with bacteria which physically perform all operators of the BFO. Secondly, a way of seamlessly embedding the bacteria from the BFO into the ABM environment is described. The bacteria are then manipulated and motivated with food and toxicity to act in a certain agent-like way. Simulation results prove that the agents can be effectively used as an ABM tool to present agents of all sizes and behaviors resembling numerous things, from companies, vehicles to people.