A Geometry-Sensitive Quorum Sensing Algorithm for the Best-of-N Site Selection Problem

The house hunting behavior of the Temnothorax albipennis ant allows colony to explore several nest choices and agree on best one. Their serves as basis for many bio-inspired swarm models solve same problem. However, existing site selection in both insect literature test model’s accuracy decision time only setups where all potential are equidistant from swarm’s starting location. These do not account geographic challenges that result with different geometry. For example, although actual colonies capable consistently choosing a higher quality, further instead lower closer site, much less accurate this scenario. Existing also more prone committing low quality if it is path between agents’ site. We present new model problem verify via simulation able better handle these challenges. Our results provide insight into types face when distance taken account. work will allow swarms be robust realistic situations sites could distributed environment ways.