Download Genetic Algorithms

兔子進化的例子
物競天擇(Selection)
交配(換)(Cross Over)
突變 (Mutation)
進化
Genetic Algorithms


利用自然進化原理的一種搜尋方法。
Three Operators(ex.兔子)
1. Selection(腿、耳好)
2. Crossover
3. Mutation

Two issues
1. Encoding the problem into a chromosome
2. Defining the fitness function
一個簡單的例子
String
No.
F(x)=x2 Fi/Σf
Initial
X
(
population value fitness)
1
2
3
4
01101
11000
01000
10011
Sum
Average
Max
13
24
8
19
169
576
64
361
1170
293
576
0.14
0.49
0.06
0.31
1.00
0.25
0.49
Fi/avg.(f) Roulette
(expected) wheel
(actual)
0.58
1.97
0.22
1.23
4.00
1.00
1.97
1
2
0
1
4.0
1.0
2.0
一個簡單的例子(continued)
Mating
Pool
Mate
Crossover
New
site
population
X value
F(x)=x2
01101
2
4
01100
12
144
11000
1
4
11001
25
625
11000
4
2
11011
27
729
10011
3
2
10000
16
256
Sum=1754
Average=439
Max=729
名詞對照(cf. Goldberg 1989)
Natural
Genetic Algorithm
Chromosome
String
Gene
Feature, character
Allele
Feature value
Locus
String position
Genotype
Structure
Phenotype
A decoded structure