DocumentCode
1634812
Title
Four problems for which a computer program evolved by genetic programming is competitive with human performance
Author
Koza, John R. ; Bennett, Forrest H., III ; Andre, David ; Keane, Martin A.
Author_Institution
Dept. of Comput. Sci., Stanford Univ., CA, USA
fYear
1996
Firstpage
1
Lastpage
10
Abstract
It would be desirable if computers could solve problems without the need for humans to write the detailed programmatic steps. That is, it would be desirable to have a domain independent automatic programming technique in which “What You Want Is What You Get” (WYWIWYG). Genetic programming is such a technique. This paper surveys three examples of problems (from the fields of cellular automata and molecular biology) in which genetic programming evolved a computer program that produced results that were slightly better than human performance for the same problem. This paper then discusses the problem of electronic circuit synthesis in greater detail. It shows how genetic programming can evolve both the topology of a desired electrical circuit and the sizing (numerical values) for each component in a crossover (woofer and tweeter) filter. Genetic programming has also evolved the design for a lowpass filter, the design of an amplifier, and the design for an asymmetric bandpass filter that was described as being difficult-to-design
Keywords
automatic programming; biology computing; cellular automata; circuit CAD; computer aided software engineering; filters; genetic algorithms; WYWIWYG; What You Want Is What You Get; amplifier; asymmetric bandpass filter; cellular automata; circuit sizing; crossover filter; electronic circuit synthesis; genetic programming; human performance; independent automatic programming; lowpass filter; molecular biology; numerical values; Automatic programming; Band pass filters; Biology computing; Cells (biology); Computer science; Electronic circuits; Genetic algorithms; Genetic mutations; Genetic programming; Humans;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
Conference_Location
Nagoya
Print_ISBN
0-7803-2902-3
Type
conf
DOI
10.1109/ICEC.1996.542327
Filename
542327
Link To Document