A novel artificial neural network trained using evolutionary algorithms for reinforcement learning

A. Reddipogu, G. Maxwell, C. MacLeod, M. Simpson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper discusses the development of a novel pattern recognition system using artificial neural networks (ANNs) and evolutionary algorithms for reinforcement learning (EARL). The network is based on neuronal interactions involved in identification of prey and predator in toads. The distributed neural network (DNN) is capable of recognizing and classifying various features. The lateral inhibition between the output neurons helps the network in the classification process - similar to the gate in gating network. The results obtained are compared with standard neural network architectures and learning algorithms.

Original languageEnglish
Title of host publicationICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing
Subtitle of host publicationComputational Intelligence for the E-Age
EditorsKunihiko Fukushima, Lipo Wang, Jagath C. Rajapakse, Soo-Young Lee, Xin Yao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1946-1950
Number of pages5
ISBN (Electronic)9810475241, 9789810475246
DOIs
Publication statusPublished - 2002
Event9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore
Duration: 18 Nov 200222 Nov 2002

Publication series

NameICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age
Volume4

Conference

Conference9th International Conference on Neural Information Processing, ICONIP 2002
Country/TerritorySingapore
CitySingapore
Period18/11/0222/11/02

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