RosettaCodeData/Task/Evolutionary-algorithm/Julia/evolutionary-algorithm.jl

25 lines
995 B
Julia

fitness(a::AbstractString, b::AbstractString) = count(l == t for (l, t) in zip(a, b))
function mutate(str::AbstractString, rate::Float64)
L = collect(Char, " ABCDEFGHIJKLMNOPQRSTUVWXYZ")
return map(str) do c
if rand() < rate rand(L) else c end
end
end
function evolve(parent::String, target::String, mutrate::Float64, nchild::Int)
println("Initial parent is $parent, its fitness is $(fitness(parent, target))")
gens = 0
while parent != target
children = collect(mutate(parent, mutrate) for i in 1:nchild)
bestfit, best = findmax(fitness.(children, target))
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
evolve("IU RFSGJABGOLYWF XSMFXNIABKT", "METHINKS IT IS LIKE A WEASEL", 0.08998, 100)