The probably approximately correct (PAC) population size of a genetic algorithm

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	Similar Articles Articles by A. Hernandez-Aguirre Articles by B.P. Buckles Articles by A. Martinez-Alcantara

12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00)

Vancouver, British Columbia, Canada

November 13-November 15

ISBN: 0-7695-0909-6

	ASCII Text	x
	A. Hernandez-Aguirre, B.P. Buckles, A. Martinez-Alcantara, "The probably approximately correct (PAC) population size of a genetic algorithm," Tools with Artificial Intelligence, IEEE International Conference on, pp. 0199, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000.

	BibTex	x
	@article{ 10.1109/TAI.2000.889870, author = {A. Hernandez-Aguirre and B.P. Buckles and A. Martinez-Alcantara}, title = {The probably approximately correct (PAC) population size of a genetic algorithm}, journal ={Tools with Artificial Intelligence, IEEE International Conference on}, volume = {0}, year = {2000}, isbn = {0-7695-0909-6}, pages = {0199}, doi = {http://doi.ieeecomputersociety.org/10.1109/TAI.2000.889870}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Tools with Artificial Intelligence, IEEE International Conference on TI - The probably approximately correct (PAC) population size of a genetic algorithm SN - 0-7695-0909-6 SP EP A1 - A. Hernandez-Aguirre, A1 - B.P. Buckles, A1 - A. Martinez-Alcantara, PY - 2000 KW - probability; genetic algorithms; learning by example; probably approximately correct; PAC population size; genetic algorithm; PAC-learning; learnability; learning machines; approximately correct behavior; PAC framework; GA population VL - 0 JA - Tools with Artificial Intelligence, IEEE International Conference on ER -

A. Hernandez-Aguirre, Dept. of Electr. Eng. & Comput. Sci., Tulane Univ., New Orleans, LA, USA

B.P. Buckles, Dept. of Electr. Eng. & Comput. Sci., Tulane Univ., New Orleans, LA, USA

A. Martinez-Alcantara, Dept. of Electr. Eng. & Comput. Sci., Tulane Univ., New Orleans, LA, USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TAI.2000.889870

Abstract: Probably approximately correct learning, PAC-learning, is a framework for the study of learnability and learning machines. In this framework, learning is induced through a set of examples. The size of this set is such that with probability greater than 1-/spl delta/ the learning machine shows an approximately correct behavior with error no greater than /spl epsiv/. The authors use the PAC framework to derive the size of a GA population that with probability 1-/spl delta/ contains at least one individual /spl epsiv/-close to a target hypothesis or solution.

Index Terms:

probability; genetic algorithms; learning by example; probably approximately correct; PAC population size; genetic algorithm; PAC-learning; learnability; learning machines; approximately correct behavior; PAC framework; GA population

Citation:

A. Hernandez-Aguirre, B.P. Buckles, A. Martinez-Alcantara, "The probably approximately correct (PAC) population size of a genetic algorithm," ictai, pp.0199, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000

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