A Neural Approach for Solving the Constraint Satisfaction Problem

	This Article
	Subscribers, please Login Purchase article: $19 PDF IEEE Xplore Subscribers RSS feed
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by S. Hamissi Articles by M. Babes

2003 International Conference on Geometric Modeling and Graphics (GMAG'03)

London, England

July 16-July 18

ISBN: 0-7695-1985-7

	ASCII Text	x
	S. Hamissi, M. Babes, "A Neural Approach for Solving the Constraint Satisfaction Problem," Geometric Modeling and Graphics, International Conference on, pp. 96, 2003 International Conference on Geometric Modeling and Graphics (GMAG'03), 2003.

	BibTex	x
	@article{ 10.1109/GMAG.2003.1219672, author = {S. Hamissi and M. Babes}, title = {A Neural Approach for Solving the Constraint Satisfaction Problem}, journal ={Geometric Modeling and Graphics, International Conference on}, volume = {0}, year = {2003}, isbn = {0-7695-1985-7}, pages = {96}, doi = {http://doi.ieeecomputersociety.org/10.1109/GMAG.2003.1219672}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Geometric Modeling and Graphics, International Conference on TI - A Neural Approach for Solving the Constraint Satisfaction Problem SN - 0-7695-1985-7 SP EP A1 - S. Hamissi, A1 - M. Babes, PY - 2003 KW - Constraint Satisfaction Problem KW - Neural Networks KW - Artificial Intelligence KW - Heuristics VL - 0 JA - Geometric Modeling and Graphics, International Conference on ER -

S. Hamissi, Universit? Badji Mokhtar

M. Babes, Universit? Badji Mokhtar

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/GMAG.2003.1219672

The realized work consists in modeling and solving a constraint satisfaction problem (CSP) by a neural approach. We intend to develop an algorithm based on the conception of a basic neural network able to solve some instantiations of the CSP. The variables are associated to the input and the output nodes of the network and the constraints correspond to the nodes of the hidden layers. The obtained results show that the network can be trapped in local minima. Therefore, we intend to modify the way of calculating the weights of the input layer, so as to improve the structure of the network initially conceived.

Index Terms:

Constraint Satisfaction Problem, Neural Networks, Artificial Intelligence, Heuristics

Citation:

S. Hamissi, M. Babes, "A Neural Approach for Solving the Constraint Satisfaction Problem," gmag, pp.96, 2003 International Conference on Geometric Modeling and Graphics (GMAG'03), 2003

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.