Sync

Task/Evolutionary-algorithm/Aime/evolutionary-algorithm.aime

@@ -0,0 +1,83 @@
+integer
+fitness(data t, data b)
+{
+    integer f, i;
+
+    f = 0;
+
+    i = b_length(t);
+    while (i) {
+        i -= 1;
+        f += sign(b_character(t, i) ^ b_character(b, i));
+    }
+
+    return f;
+}
+
+void
+mutate(data c, data b, data u)
+{
+    integer i, l;
+
+    l = b_length(b);
+    i = 0;
+    while (i < l) {
+        if (drand(15)) {
+            b_append(c, b_character(b, i));
+        } else {
+            b_append(c, b_character(u, drand(26)));
+        }
+        i += 1;
+    }
+}
+
+integer
+main(void)
+{
+    data b, t, u;
+    integer f, i, l;
+
+    b_cast(t, "METHINK IT IS LIKE A WEASEL");
+    b_cast(u, "ABCDEFGHIJKLMNOPQRSTUVWXYZ ");
+
+    l = b_length(t);
+
+    i = l;
+    while (i) {
+        i -= 1;
+        b_append(b, b_character(u, drand(26)));
+    }
+
+    f = fitness(t, b);
+    while (f) {
+        data n;
+        integer a;
+
+        o_winteger(-4, f);
+        o_text(b_string(b));
+        o_newline();
+
+        n = b;
+
+        i = 32;
+        while (i) {
+            data c;
+
+            i -= 1;
+            mutate(c, b, u);
+            a = fitness(t, c);
+            if (a < f) {
+                f = a;
+                n = c;
+            }
+        }
+
+        b = n;
+    }
+
+    o_winteger(-4, f);
+    o_text(b_string(b));
+    o_newline();
+
+    return 0;
+}

Task/Evolutionary-algorithm/D/evolutionary-algorithm.d

@@ -10,7 +10,7 @@ enum mut= (dchar[] s) => s.map!(a=> uniform(0,1.) < P ? rnd : a).array;
 void main() {
     auto parent = target.length.iota.map!(_ => rnd).array;
     for (auto gen = 1; parent != target; gen++) {
-        //parent = parent.repeat(C).map!mut.array.max!(s => s.fitness);
+        // parent = parent.repeat(C).map!mut.array.max!fitness;
         parent = parent.repeat(C).map!mut.array
                  .minPos!((a, b) => a.fitness < b.fitness)[0];
         writefln("Gen %2d, dist=%2d: %s", gen, parent.fitness, parent);

Task/Evolutionary-algorithm/Haskell/evolutionary-algorithm-1.hs

@@ -4,7 +4,7 @@ import Data.List
 import Data.Ord
 import Data.Array
 
-showNum :: (Num a) => Int -> a -> String
+showNum :: (Num a, Show a) => Int -> a -> String
 showNum w = until ((>w-1).length) (' ':) . show
 
 replace :: Int -> a -> [a] -> [a]

Task/Evolutionary-algorithm/Haskell/evolutionary-algorithm-2.hs

@@ -1,5 +1,4 @@
-import System
-import Random
+import System.Random
 import Data.List
 import Data.Ord
 import Data.Array

Task/Evolutionary-algorithm/PHP/evolutionary-algorithm.php

@@ -0,0 +1,45 @@
+define('TARGET','METHINKS IT IS LIKE A WEASEL');
+define('TBL','ABCDEFGHIJKLMNOPQRSTUVWXYZ ');
+
+define('MUTATE',15);
+define('COPIES',30);
+define('TARGET_COUNT',strlen(TARGET));
+define('TBL_COUNT',strlen(TBL));
+
+// Determine number of different chars between a and b
+
+function unfitness($a,$b)
+{
+        $sum=0;
+        for($i=0;$i<strlen($a);$i++)
+                if($a[$i]!=$b[$i]) $sum++;
+        return($sum);
+}
+
+function mutate($a)
+{
+        $tbl=TBL;
+        for($i=0;$i<strlen($a);$i++) $out[$i]=mt_rand(0,MUTATE)?$a[$i]:$tbl[mt_rand(0,TBL_COUNT-1)];
+        return(implode('',$out));
+}
+
+
+$tbl=TBL;
+for($i=0;$i<TARGET_COUNT;$i++) $tspec[$i]=$tbl[mt_rand(0,TBL_COUNT-1)];
+$parent[0]=implode('',$tspec);
+$best=TARGET_COUNT+1;
+$iters=0;
+do {
+        for($i=1;$i<COPIES;$i++) $parent[$i]=mutate($parent[0]);
+
+        for($best_i=$i=0; $i<COPIES;$i++) {
+                $unfit=unfitness(TARGET,$parent[$i]);
+                if($unfit < $best || !$i) {
+                        $best=$unfit;
+                        $best_i=$i;
+                }
+        }
+        if($best_i>0) $parent[0]=$parent[$best_i];
+        $iters++;
+        print("Generation $iters, score $best: $parent[0]\n");
+} while($best);

Task/Evolutionary-algorithm/Perl-6/evolutionary-algorithm.pl6

@@ -4,7 +4,7 @@ constant alphabet = 'A'..'Z',' ';
 constant C = 100;
 
 sub mutate { $^string.comb.map({ rand < mutate_chance ?? alphabet.pick !! $_ }).join }
-sub fitness { [+] $^string.comb Zeq target.comb }
+sub fitness { [+] $^string.comb Zeq state @ = target.comb }
 
 loop (
     my $parent = alphabet.roll(target.chars).join;

Task/Evolutionary-algorithm/Visual-Basic/evolutionary-algorithm.vb

@@ -0,0 +1,60 @@
+Option Explicit
+
+Private Sub Main()
+   Dim Target
+   Dim Parent
+   Dim mutation_rate
+   Dim children
+   Dim bestfitness
+   Dim bestindex
+   Dim Index
+   Dim fitness
+
+      Target = "METHINKS IT IS LIKE A WEASEL"
+      Parent = "IU RFSGJABGOLYWF XSMFXNIABKT"
+      mutation_rate = 0.5
+       children = 10
+      ReDim child(children)
+
+      Do
+        bestfitness = 0
+        bestindex = 0
+        For Index = 1 To children
+          child(Index) = FNmutate(Parent, mutation_rate, Target)
+          fitness = FNfitness(Target, child(Index))
+          If fitness > bestfitness Then
+            bestfitness = fitness
+            bestindex = Index
+          End If
+        Next Index
+
+        Parent = child(bestindex)
+        Debug.Print Parent
+      Loop Until Parent = Target
+      End
+
+
+End Sub
+
+Function FNmutate(Text, Rate, ref)
+   Dim C As Integer
+   Dim Aux As Integer
+
+     If Rate > Rnd(1) Then
+        C = 63 + 27 * Rnd() + 1
+        If C = 64 Then C = 32
+        Aux = Len(Text) * Rnd() + 1
+        If Mid(Text, Aux, 1) <> Mid(ref, Aux, 1) Then
+            Text = Left(Text, Aux - 1) & Chr(C) & Mid(Text, Aux + 1)
+        End If
+
+     End If
+      FNmutate = Text
+End Function
+Function FNfitness(Text, ref)
+    Dim I, F
+      For I = 1 To Len(Text)
+        If Mid(Text, I, 1) = Mid(ref, I, 1) Then F = F + 1
+      Next
+      FNfitness = F / Len(Text)
+End Function