Modeling honeybee communication using network of spiking neural networks to simulate nectar reporting behavior

Abstract

The paper presents the findings of the research that attempted to mathematically model the cognitive behavior that could arise due to the interaction between honeybees in a colony during forager recruitment process. The model defines a honeybee as a spiking neural network, and colony as a network of spiking neural networks. The proposed mathematical model has been evaluated by analyzing the cognitive behavior generated by the main network which represents honeybees’ interaction as interactions of component networks (i.e. spiking neural networks). Accordingly, behavior of the component network, that represents an unemployed forager in the colony, was examined under different scenarios by setting networks’ parameters to simulate ecological situations in the colony. The reporting of different level of quantity of nectar sources by scouts to the colony, an attempt made by a scout to attract more unemployed foragers for foraging, and influence by dancing foragers to attract other unemployed foragers for foraging are those ecological colony states that have been tested in this research. The results of all these cases have supported that the proposed mathematical model can sufficiently simulate the unemployed forager’s behavior during recruitment process.