Influence of a Social Gradient on a Swarm of Agents Controlled by the BEECLUST Algorithm

Abstract

Agents controlled by a swarm algorithm interact with each other so that they have collective capabilities that a sin-gle 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 differ-ent 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 environ-ment. It shows that the robots controlled by the BEECLUST-algorithm are able to react on a social stimulus within an en-vironment with a global and a local optimum. Background & Motivation