Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks

Authors:
Nicolas Oros;Volker Steuber;Neil Davey;Lola Cañamero;Rod Adams
Affiliations:
Science and Technology Research Institute, University of Hertfordshire, United Kingdom AL10 9AB;Science and Technology Research Institute, University of Hertfordshire, United Kingdom AL10 9AB;Science and Technology Research Institute, University of Hertfordshire, United Kingdom AL10 9AB;Science and Technology Research Institute, University of Hertfordshire, United Kingdom AL10 9AB;Science and Technology Research Institute, University of Hertfordshire, United Kingdom AL10 9AB
Venue:
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Year:
2008

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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.