Title :
Stack-based genetic programming
Author_Institution :
Antelope Eng., Albany, CA, USA
Abstract :
Some recent work in the field of genetic programming (GP) has been concerned with finding optimum representations for evolvable and efficient computer programs. This paper describes a new GP system in which target programs run on a stack-based virtual machine. The system is shown to have certain advantages in terms of efficiency and simplicity of implementation, and for certain problems, its effectiveness is shown to be comparable or superior to current methods
Keywords :
genetic algorithms; learning (artificial intelligence); optimisation; optimum representations; stack-based genetic programming; stack-based virtual machine; Assembly; Genetic engineering; Genetic programming; Protection; Shape; Tagging; Virtual machining;
Conference_Titel :
Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1899-4
DOI :
10.1109/ICEC.1994.350025
