Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks

TitleAdaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks
Publication TypeConference Paper
Year of Publication2008
AuthorsOros, N, Steuber, V, Davey, N, Cañamero, L, Adams, RG
EditorAsada, M, Hallam, JCT, Meyer, J-A, Tani, J
Name of ProceedingsFrom Animals to Animats 10: Proc. 10th International Conference on Simulation of Adaptive Behavior (SAB 2008)
Series TitleLecture Notes in Computer Science (LNCS)
Series Volume 5040
Date Published07/2008
PublisherSpringer, Berlin, Heidelberg
Conference LocationOsaka, Japan
ISBN Number978-3-540-69134-1

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.