Flocking Behavior for Multi-Agent Systems With Cooperation-Competition Evolution

In numerous applications of multi-agent systems (MASs), e.g., social networks and biological networks, the relationship between agents may shift from competition to cooperation or vice versa. With that in mind, this paper investigates flocking behavior of MASs with evolving cooperation-competition relationships. The relationship between neighboring agents is characterized by a state-dependent nonlinear function: competition is triggered when the state discrepancy between agents exceeds a predefined threshold, whereas cooperation is maintained otherwise. A complete analysis is conducted on flocking behavior using the infinite products of substochastic matrices. As algebraic conditions regarding agent states and cooperative ranges are established to ensure the emergence of flocking behavior, and a lower bound for the convergence rate of flocking behavior is established. Finally, the theoretical results are validated through numerical simulations and an indoor multi-UAV system platform.