ISSN:
1573-7632
Keywords:
genetic algorithms
;
genetic programming
;
bloat reduction
;
evolution of shape
;
subquadratic length growth
;
linear depth growth
;
uniform initialization
;
binary tree search spaces
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
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 (i.e., less bloat) and no detrimental effect on GP performance. GP search spaces are partitioned by the ridge in the number of program v. 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 initialization is described which straddles the ridge. With subtree crossover trees increase about one level per generation leading to subquadratic bloat in program length.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1010024515191
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