SWAM INTELLIGENCE Swarm-intelligent foraging in honeybees: benefits and costs of task-partitioning and environmental fluctuations

Abstract For honeybee colonies, it is crucial to collect nectar in an efficient way. Empiric experiments showed that the process of decision making, which allows the colony to select the optimal nectar source, is based on individual decisions. These decisions are made by return-ing nectar foragers, which alter their dancing behaviours based on the nectar source’s quality and based on the experienced search time for a receiver bee. Nectar receiv-ers, which represent a shared limited resource for foragers, can modulate the foraging decisions performed by the colony. We investigated the interplay between foragers and receivers by using a multi-agent simulation. Therefore, we implemented agents which are capable of a limited set of behaviours and which spend energy according to their behaviour. In simulation experiments, we tested colonies with various receiver-to-forager ratios and measured col-ony-level results like the emerging foraging patterns and the colony’s net honey gain. We show that the number of receivers prominently regulates the foraging workforce. All tested environmental fluctuations are predicted to cause energetic costs for the colony. Task-partitioning addition-ally influences the colony’s decision-making concerning the question whether or not the colony sticks to a nectar source after environmental fluctuations