- author = "Terence Soule",
- title = "Code Growth in Genetic Programming",
- school = "University of Idaho",
- year = "1998",
- address = "Moscow, Idaho, USA",
- month = "15 " # may,
- keywords = "genetic algorithms, genetic programming, bloat",
-
URL = "
http://www.cs.uidaho.edu/~tsoule/research/the3.ps",
- size = "101 pages",
-
abstract = "Genetic programming is a technique for the automatic
generation of computer programs loosely based on the
theory of evolution. It has produced successful
solutions to a wide variety of problems and can be
effective even in noisy and changing
environments.
However, genetic programming produces solutions with large amounts of unnecessary code. The amount of unnecessary code increases over time and is not proportional to increases in the quality of the solutions produced. Thus, this additional code seriously hinders the genetic programming processes by requiring extra resources without producing equivalent returns.
This dissertation examines the causes of this code growth. We use three test problems from very different fields of interest to confirm the generality of the results. We tested the destructive hypothesis, that code growth is a protective response to the destructiveness of crossover, as a potential cause of code growth. It is a definite cause, but is not sufficient to explain all growth. We propose a second cause of code growth removal bias to explain the remaining growth. Testing shows that removal bias does occur and that it produces growth sufficient to explain the discrepancy. We also examine the relationship between code size and code shape, demonstrating that sparser program trees produce more rapid growth. Finally, we examine parsimony pressure as a potential solution to the code growth phenomenon.",
