Data update

Task/Evolutionary-algorithm/Elena/evolutionary-algorithm.elena

@@ -27,39 +27,39 @@ extension evoHelper
 
 class EvoAlgorithm : Enumerator
 {
-    object theTarget;
-    object theCurrent;
-    object theVariantCount;
+    object _target;
+    object _current;
+    object _variantCount;
 
     constructor new(s,count)
     {
-        theTarget := s;
-        theVariantCount := count.toInt();
+        _target := s;
+        _variantCount := count.toInt();
     }
 
-    get() = theCurrent;
+    get Value() = _current;
 
     bool next()
     {
-        if (nil == theCurrent)
-            { theCurrent := theTarget.Length.randomString(); ^ true };
+        if (nil == _current)
+            { _current := _target.Length.randomString(); ^ true };
 
-        if (theTarget == theCurrent)
+        if (_target == _current)
             { ^ false };
 
-        auto variants := Array.allocate(theVariantCount).populate:(x => theCurrent.mutate:P );
+        auto variants := Array.allocate(_variantCount).populate:(x => _current.mutate:P );
 
-        theCurrent := variants.sort:(a,b => a.fitnessOf:Target > b.fitnessOf:Target ).at:0;
+        _current := variants.sort:(a,b => a.fitnessOf:Target > b.fitnessOf:Target ).at:0;
 
         ^ true
     }
 
     reset()
     {
-        theCurrent := nil
+        _current := nil
     }
 
-    enumerable() => theTarget;
+    enumerable() => _target;
 }
 
 public program()

Task/Evolutionary-algorithm/Icon/evolutionary-algorithm-2.icon

@@ -0,0 +1,7 @@
+(var c 100)  ;number of children in each generation
+(var p 0.05) ;mutation probability
+
+(var target "METHINKS IT IS LIKE A WEASEL")
+(var tsize (len target))
+
+(var alphabet (to-vec " ABCDEFGHIJLKLMNOPQRSTUVWXYZ"))

Task/Evolutionary-algorithm/Icon/evolutionary-algorithm-3.icon

@@ -0,0 +1,5 @@
+(var fitness (comp @(map = target) (count val)))
+(var perfect-fit? (comp fitness (= tsize)))
+
+(var rand-char #(rand-pick alphabet))
+(var mutate (map #(if (< (rand) p) (rand-char) %)))

Task/Evolutionary-algorithm/Icon/evolutionary-algorithm-4.icon

@@ -0,0 +1,12 @@
+(function evolve generation parent
+
+  (print (pad-left " " 3 generation) " " (... str parent) " " (fitness parent))
+
+  (return-when (perfect-fit? parent))
+
+  (let children (times c #(mutate parent))
+       fittest  (max-by fitness (... vec parent children)))
+
+  (recur (inc generation) fittest))
+
+(evolve 1 (times tsize rand-char))