DocumentCode
3252582
Title
A genetic approach to the truck backer upper problem and the inter-twined spiral problem
Author
Koza, John R.
Author_Institution
Dept. of Comput. Sci., Stanford Univ., CA, USA
Volume
4
fYear
1992
fDate
7-11 Jun 1992
Firstpage
310
Abstract
The author describes a biologically motivated paradigm, genetic programming, which can solve a variety of problems. When genetic programming solves a problem, it produces a computer program that takes the state variables of the system as input and produces the actions required to solve the problem as output. Genetic programming is explained and applied to two well-known benchmark problems from the field of neural networks. The truck backer upper problem is a multidimensional control problem and the inter-twined spirals problem is a challenging classification problem
Keywords
genetic algorithms; multidimensional systems; position control; classification; genetic programming; inter-twined spirals problem; multidimensional control; truck backer upper problem; Artificial neural networks; Biology; Computer science; Genetic algorithms; Genetic programming; Learning; Neural networks; Problem-solving; Shape; Spirals;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location
Baltimore, MD
Print_ISBN
0-7803-0559-0
Type
conf
DOI
10.1109/IJCNN.1992.227324
Filename
227324
Link To Document