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