Agents controlled by a swarm algorithm interact with each other so that they have collective capabilities that a single agent does not have. The bio-inspired swarm-algorithm “BEECLUST” has the aim to aggregate a swarm at the global optimum even if there are several local optima (of the same type) present. But what about gradients produced of different stimulus types? In this paper, we present the concept of “social stimuli”. We investigate how robots controlled by
the BEECLUST-algorithm react to a social stimulus which is created by placing immobilized robots in the environment. It shows that the robots controlled by the BEECLUST-algorithm are able to react on a social stimulus within an environment with a global and a local optimum.