Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks
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Author
Oros, N.
Steuber, Volker
Davey, N.
Canamero, L.
Adams, R.G.
Attention
2299/2422
Abstract
We created a neural architecture that can use two different types of information encoding strategies depending on the environment. The goal of this research was to create a simulated agent that could react to two different overlapping chemicals having varying concentrations. The neural network controls the agent by encoding its sensory information as temporal coincidences in a low concentration environment, and as firing rates at high concentration. With such an architecture, we could study synchronization of firing in a simple manner and see its effect on the agent’s behaviour.