Initial data commit

Task/Evolutionary-algorithm/Java/evolutionary-algorithm.java

@@ -0,0 +1,58 @@
+import java.util.Random;
+
+public class EvoAlgo {
+  static final String target = "METHINKS IT IS LIKE A WEASEL";
+  static final char[] possibilities = "ABCDEFGHIJKLMNOPQRSTUVWXYZ ".toCharArray();
+  static int C = 100; //number of spawn per generation
+  static double minMutateRate = 0.09;
+  static int perfectFitness = target.length();
+  private static String parent;
+  static Random rand = new Random();
+
+  private static int fitness(String trial){
+    int retVal = 0;
+    for(int i = 0;i < trial.length(); i++){
+      if (trial.charAt(i) == target.charAt(i)) retVal++;
+    }
+    return retVal;
+  }
+
+  private static double newMutateRate(){
+    return (((double)perfectFitness - fitness(parent)) / perfectFitness * (1 - minMutateRate));
+  }
+
+  private static String mutate(String parent, double rate){
+    String retVal = "";
+    for(int i = 0;i < parent.length(); i++){
+      retVal += (rand.nextDouble() <= rate) ?
+        possibilities[rand.nextInt(possibilities.length)]:
+        parent.charAt(i);
+    }
+    return retVal;
+  }
+
+  public static void main(String[] args){
+    parent = mutate(target, 1);
+    int iter = 0;
+    while(!target.equals(parent)){
+      double rate = newMutateRate();
+      iter++;
+      if(iter % 100 == 0){
+        System.out.println(iter +": "+parent+ ", fitness: "+fitness(parent)+", rate: "+rate);
+      }
+      String bestSpawn = null;
+      int bestFit = 0;
+      for(int i = 0; i < C; i++){
+        String spawn = mutate(parent, rate);
+        int fitness = fitness(spawn);
+        if(fitness > bestFit){
+          bestSpawn = spawn;
+          bestFit = fitness;
+        }
+      }
+      parent = bestFit > fitness(parent) ? bestSpawn : parent;
+    }
+    System.out.println(parent+", "+iter);
+  }
+
+}