NDLI: Genetic task clustering for modular neural networks

Content Provider	IEEE Xplore Digital Library
Author	Drabe, T. Bressgott, W. Bartscht, E.
Copyright Year	1996
Description	Author affiliation: SIBET GmbH, Hannover, Germany (Drabe, T.)
Abstract	This paper introduces a method to cluster subtasks of a complex task to be learned by neural networks. The main objectives are minimization of the epochs needed to train the clusters up to a specified error limit and to maximize the generalization rates of the trained networks. To cope with the combinatorial optimization problem involved a genetic algorithm is developed. It starts with a set of random clusters which are trained up to a stopping criterion. Based on a fitness measure derived from the training results, new clusters are assembled using genetic operators. The approach of this work is relevant for all problems being decomposable into distinct subtasks, for example in robotics and plant control, where piecewise control strategies can be learned, and in image processing. Simulations for letter recognition indicate that the method is superior to both training all tasks on large monolithic network and to training randomly assigned clusters on small modular networks.
Starting Page	339
Ending Page	347
File Size	466775
Page Count	9
File Format	PDF
ISBN	0818674563
DOI	10.1109/NICRSP.1996.542777
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-08-21
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robotic assembly Neural network hardware Network topology Image processing Neural networks Robot control Genetic mutations Space exploration Genetic algorithms Fuzzy systems
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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