Variation as an element in multi-agent control for target tracking

This work investigates the impact of inter-agent variation on the performance of a multi-agent system based control system. The control system is composed of a multi-agent team and aggregates the actions of the individual agents of the team to form a single output. In the process, this approach attempts to use error and variation that naturally occurs in physical systems to the system´s advantage. We apply this multi-agent control system to a multiple task allocation problem and present an analytical model with which we can study the conditions under which such a system is expected to stabilize. We then compare the expected behavior of the analytical model with an empirical agent-based simulation applied to a tracking problem.