Abstract
This thesis investigates a number of hybrid adaptive strategies to drive multi-agent systems from initial states of disorder towards consensus or favourable configurations. The dynamics of the agents and their communicative links, represented by nonlinear ODEs, may be visualised as evolving networks. Numerical experiments supplement the mathematical models presented.