Title

Evolving Spiking Neural Networks of artificial creatures using Genetic Algorithm

Document Type

Conference Proceeding

Publication Date

10-31-2016

Publication Title

Proceedings of the International Joint Conference on Neural Networks

Volume

2016-October

First Page

411

Last Page

418

Abstract

This paper presents a Genetic Algorithm (GA) based evolution framework in which Spiking Neural Network (SNN) of single or a colony of artificial creatures are evolved for higher chance of survival in a virtual environment. The artificial creatures are composed of randomly connected Izhikevich spiking reservoir neural networks. Inspired by biological neurons, the neuronal connections are considered with different axonal conduction delays. Simulation results prove that the evolutionary algorithm has the capability to find or synthesis artificial creatures which can survive in the environment successfully and also simulations verify that colony approach has a better performance in comparison with a single complex creature.

DOI

10.1109/IJCNN.2016.7727228

ISBN

9781509006199

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