| Following the discovery of an odor-processing neuron in the honeybee brain, Montague and colleagues developed a computer model accurately reproducing honeybee foraging in uncertain environments. This thesis describes an extended model which adds olfaction for robustness and sensory focusing for a closer representation to a real honeybee. The model bee exhibits temporal difference (TD) learning through a feed-forward neural network with hebbian learning. By adding the sense of olfaction, the model becomes more robust so learning occurs with both senses and with vision or olfaction disabled. Through the new focusing algorithm for each sense, the model bee's guidance is more precise, while simultaneously representing a real honeybee's focusing ability. In simulations, the model bee behaved similarly to a real honeybee with exceptions due to narrow focusing for which a modified focusing algorithm is proposed. Results suggest applications for real-world search engines. |
