RosettaCodeData/Task/Evolutionary-algorithm/Julia/evolutionary-algorithm-1.julia

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function evolve(parent,target,mutation_rate,num_children)
println("Initial parent is $parent, its fitness is $(fitness(parent,target))")
gens=0
while parent!=target
children=[mutate(parent,mutation_rate) for i=1:num_children]
bestfit,best=findmax(map(child->fitness(child,target),children))
parent=children[best]
gens+=1
if gens%10==0
println("After $gens generations, the new parent is $parent and its fitness is $(fitness(parent,target))")
end
end
println("After $gens generations, the parent evolved into the target $target")
end
fitness(s1,s2)=count(x->x,convert(Array{Char,1},s1).==convert(Array{Char,1},s2))
function mutate(s,rate)
new_s=""
for c in s
new_s*=string(rand()<rate?
" ABCDEFGHIJKLMNOPQRSTUVWXYZ"[rand(1:27)]:c)
end
return new_s
end
evolve("IU RFSGJABGOLYWF XSMFXNIABKT","METHINKS IT IS LIKE A WEASEL",0.08998,100)