Swarm intelligence,
in some ways, may be viewed as an extension of cellular automata, where they deposit evanescent pheremone trails on the return journey after a successful trip. In effect, they are providing a time-decaying positive feedback mechanism to reinforce the better outcomes for randomised searches for local optima and by extension will tend towards a global optimum - through an attempted optimal combination of local optima. The time-decaying feedback allows the system to adapt dynamically to changing circumstances and avoids getting stuck in local minima.Another option is to view them as quasi-optmised probabilistic searches over space and time, which avoid getting stuck in local optima.