Stable emergent heterogeneous agent distributions in noisy environments

Abstract

A mathematical model is introduced for the study of the behavior of a spatially distributed group of heterogenous agents which possess noisy assessments of the state of their immediate surroundings. We define general sensing and motion conditions on the agents that guarantee the emergence of a type of "ideal free distribution" (IFD) across the environment, and focus on how individual and environmental characteristics affect this distribution. In particular, we show the impact of the agents' maneuvering and sensing abilities for different classes of environments, and how spatial constraints of the environment affect the rate at which the distribution is achieved. Finally, we apply this model to a cooperative vehicle control problem and present simulation results that show the benefits of an IFD-based distributed decision-making strategy