A construction of neural-net based AI systems

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First IEEE International Conference on Engineering of Complex Computer Systems (ICECCS'95)

Ft. Lauderdale, Florida

November 06-November 10

ISBN: 0-8186-7123-8

	ASCII Text	x
	M. Kawada, Xu Wu, T. Ae, "A construction of neural-net based AI systems," Engineering of Complex Computer Systems, IEEE International Conference on, pp. 424, First IEEE International Conference on Engineering of Complex Computer Systems (ICECCS'95), 1995.

	BibTex	x
	@article{ 10.1109/ICECCS.1995.479369, author = {M. Kawada and Xu Wu and T. Ae}, title = {A construction of neural-net based AI systems}, journal ={Engineering of Complex Computer Systems, IEEE International Conference on}, volume = {0}, year = {1995}, isbn = {0-8186-7123-8}, pages = {424}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICECCS.1995.479369}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Engineering of Complex Computer Systems, IEEE International Conference on TI - A construction of neural-net based AI systems SN - 0-8186-7123-8 SP EP A1 - M. Kawada, A1 - Xu Wu, A1 - T. Ae, PY - 1995 KW - neural net architecture; real-time systems; case-based reasoning; pattern classification; learning (artificial intelligence); knowledge based systems; algorithm theory; neural-net based AI system construction; neural network technique; real-time neuron-based AI architecture; NAI; real-time case-based reasoning system; winner-take-all type neural network; real-time classification; real-time retrieval; massive case-base; flexible learning; learning algorithms; supervised learning; unsupervised learning; self-organizing learning algorithm; LVQ1 learning algorithm VL - 0 JA - Engineering of Complex Computer Systems, IEEE International Conference on ER -

M. Kawada, Dept. of Electron. Eng., Hiroshima Univ., Japan

Xu Wu, Dept. of Electron. Eng., Hiroshima Univ., Japan

T. Ae, Dept. of Electron. Eng., Hiroshima Univ., Japan

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICECCS.1995.479369

The paper investigates the integration of the neural network technique and traditional AI techniques towards the realization of a real-time neuron-based AI architecture. As the first step of our project, we propose a neural network based AI system, called NAI. NAI is a kind of real-time CBR (case-based reasoning) system in which the WTA (winner-take-all) type neural network is embedded for supporting the real-time classification and retrieval of a massive case-base. For flexible learning with the WTA neural network, two learning algorithms (supervised and unsupervised) have been developed on the basis of the LVQ1 and self-organizing learning algorithms.

Index Terms:

neural net architecture; real-time systems; case-based reasoning; pattern classification; learning (artificial intelligence); knowledge based systems; algorithm theory; neural-net based AI system construction; neural network technique; real-time neuron-based AI architecture; NAI; real-time case-based reasoning system; winner-take-all type neural network; real-time classification; real-time retrieval; massive case-base; flexible learning; learning algorithms; supervised learning; unsupervised learning; self-organizing learning algorithm; LVQ1 learning algorithm

Citation:

M. Kawada, Xu Wu, T. Ae, "A construction of neural-net based AI systems," iceccs, pp.424, First IEEE International Conference on Engineering of Complex Computer Systems (ICECCS'95), 1995

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