Global emergent behaviors in clouds of agents

Networks of biological agents (for example, ants, bees, fish, birds) and complex man-made cyberphysical infrastructures (for example, the power grid, transportation networks) exhibit one thing in common - the emergence of collective global phenomena from apparently random local interactions. This paper proposes a distributed graphical model of interacting agents (a stochastic network type model) and studies its appropriate asymptotics. We show that metastability may occur - i.e., under certain conditions, the agents act in synchrony and may exhibit collectively possibly different stable equilibria - these are the global emergent behaviors of the cloud of interacting agents. We characterize these global behaviors as synchronous fixed points determined from ordinary differential equations that arise as mean field limits of the adopted stochastic model.