DocumentCode :
3238124
Title :
Scatter programming
Author :
Hedar, Abdel-Rahman ; Osman, Mostafa Kamel
Author_Institution :
Dept. of Comput. Sci., Assiut Univ., Assiut, Egypt
fYear :
2010
fDate :
2-4 Nov. 2010
Firstpage :
451
Lastpage :
455
Abstract :
The core of artificial intelligence and machine learning is to get computers to solve problems automatically. One of the great tools that attempt to achieve that goal is Genetic Programming (GP). As alternatives to GP, Scatter Programming (SP) is proposed in this paper. One of the main features of SP is to exploit local search in order to overcome some recently addressed drawbacks of GP, especially its highly disruption of its main operations; crossover and mutation. This work shows that SP has promising performance and results in solving machine learning problems.
Keywords :
genetic algorithms; learning (artificial intelligence); artificial intelligence; genetic programming; machine learning; scatter programming; Programming; USA Councils; Genetic programming; Local search programming; Machine learning; Meta-heuristic programming; Scatter programming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Technology and Development (ICCTD), 2010 2nd International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-8844-5
Electronic_ISBN :
978-1-4244-8845-2
Type :
conf
DOI :
10.1109/ICCTD.2010.5645839
Filename :
5645839
Link To Document :
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