June 2018 Update

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

@@ -0,0 +1,24 @@
+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)