Information Technology Reference
In-Depth Information
Table 12.4
Comparing the performance of unigenic and multigenic systems on the
function finding problem.
1 Gene
3 Genes
5 Genes
Number of runs
100
100
100
Number of generations
50
50
50
Population size
30
30
30
Number of fitness cases
10
10
10
Function set
+ - * /
+ - * /
+ - * /
Head length
37
12
7
Number of genes
1
3
5
Linking function
--
+
+
Chromosome length
75
75
75
Mutation rate
0.03
0.03
0.03
One-point recombination rate
0.3
0.3
0.3
Two-point recombination rate
0.3
0.3
0.3
Gene recombination rate
--
0.1
0.1
IS transposition rate
0.1
0.1
0.1
IS elements length
1,2,3
1,2,3
1,2,3
RIS transposition rate
0.1
0.1
0.1
RIS elements length
1,2,3
1,2,3
1,2,3
Gene transposition rate
--
0.1
0.1
Selection range
25%
25%
25%
Precision
0.01%
0.01%
0.01%
Success rate
58%
93%
98%
As expected, multigenic systems are significantly more efficient than
unigenic ones and should always be our first choice. There might be prob-
lems, though, for which the fractionating of the chromosome in genes is of
little advantage. For instance, when we are trying to evolve a solution to a
problem best modeled by the logarithm or the square root function of some
complex expression and a cellular system with automatic linking was not
our first choice. But, even in those cases, the system can easily find ways of
turning the unnecessary genes into neutral genes and, therefore, an efficient
adaptation can still occur. But of course, in cellular and multicellular sys-
tems, the modeling of all kinds of functions can benefit from multiple genes
as those systems are not constrained by a particular kind of linking function.
