Abstract
We here describe a novel multi-agent model of the decentralized task selection process in honeybee colonies. The model is based on individual behavioural programs represented as hierarchical finite state automatons. We successfully simulated empirical experiments (with real honeybees) using the model. We shed more light on task specialization and polyethism in honeybees by modelling the heterogeneous environment that emerges over time inside the colony and by considering the changing differences in stimuli strength in each small area of the hive. Our simulation experiments presented here investigate the model's reaction to changing values in crucial model parameters and investigate the stability of the predicted colony behaviours.
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