Article,
Size Fair and Homologous Tree Genetic Programming Crossovers
Genetic Programming and Evolvable Machines, 1 (1/2): 95--119 (April 2000)
DOI: doi:10.1023/A:1010024515191
Abstract
Size fair and homologous crossover genetic operators
for tree based genetic programming are described and
tested. Both produce considerably reduced increases in
program size (ie less bloat) and no detrimental effect
on GP performance.
GP search spaces are partitioned by the ridge in the
number of program versus their size and depth. While
search efficiency is little effected by initial
conditions, these do strongly influence which half of
the search space is searched. However a ramped uniform
random initialisation is described which straddles the
ridge.
With subtree crossover trees increase about one level
per generation leading to sub-quadratic bloat in
program length.
Tags
- algorithms,
- binary
- bloat
- depth
- evolution
- genetic
- growth,
- initialisation,
- length
- linear
- of
- programming,
- reduction,
- search
- shape,
- spaces
- subquadratic
- tree
- uniform
