September 2017 Update

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

@@ -1,27 +1,22 @@
-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")
+function evolve(parent::String, target::String, mutrate::Float64, nchild::Int)
+    fitness(a, b::String=target) = count(l == t for (l, t) in zip(a, b))
+    function mutate(str::String, rate::Float64=mutrate)
+        L = split(" ABCDEFGHIJKLMNOPQRSTUVWXYZ", "")
+        r = collect(rand() < rate ? rand(L) : c for c in str)
+        return string(r...)
+    end
+    println("Initial parent is $parent, its fitness is $(fitness(parent))")
+    gens = 0
+    while parent != target
+        children = collect(mutate(parent, mutrate) for i in 1:nchild)
+        bestfit, best = findmax(fitness.(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))")
+        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)
+evolve("IU RFSGJABGOLYWF XSMFXNIABKT", "METHINKS IT IS LIKE A WEASEL", 0.08998, 100)