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

Thomas Schmickl, Ronald Thenius, Karl Crailsheim
Neural Computing & Application 21 (2012), 251-268


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.

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