Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks

N. Oros; Volker Steuber; N. Davey; L. Canamero; R.G. Adams

doi:10.1007/978-3-540-69134-1_15

Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks

N. Oros, Volker Steuber, N. Davey, L. Canamero, R.G. Adams

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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.

Original language	English
Pages (from-to)	148-158
Journal	Lecture Notes in Computer Science (LNCS)
Volume	5040
Issue number	From Animals to Animats 10
DOIs	https://doi.org/10.1007/978-3-540-69134-1_15
Publication status	Published - 2008

Keywords

neural encoding
firing rate
temporal coincidence

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AB - 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.

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Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks

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