Data commit

Task/Evolutionary-algorithm/Scala/evolutionary-algorithm.scala

@@ -0,0 +1,37 @@
+import scala.annotation.tailrec
+
+case class LearnerParams(target:String,rate:Double,C:Int)
+
+val chars =  ('A' to 'Z') ++ List(' ')
+val randgen = new scala.util.Random
+def randchar = {
+   val charnum = randgen.nextInt(chars.size)
+   chars(charnum)
+}
+
+class RichTraversable[T](t: Traversable[T]) {
+    def maxBy[B](fn: T => B)(implicit ord: Ordering[B]) = t.max(ord on fn)
+    def minBy[B](fn: T => B)(implicit ord: Ordering[B]) = t.min(ord on fn)
+}
+
+implicit def toRichTraversable[T](t: Traversable[T]) = new RichTraversable(t)
+
+def fitness(candidate:String)(implicit params:LearnerParams) =
+   (candidate zip params.target).map { case (a,b) => if (a==b) 1 else 0 }.sum
+
+def mutate(initial:String)(implicit params:LearnerParams) =
+   initial.map{ samechar => if(randgen.nextDouble < params.rate) randchar else samechar }
+
+@tailrec
+def evolve(generation:Int, initial:String)(implicit params:LearnerParams){
+   import params._
+   printf("Generation: %3d  %s\n",generation, initial)
+   if(initial == target) return ()
+   val candidates = for (number <- 1 to C) yield mutate(initial)
+   val next = candidates.maxBy(fitness)
+   evolve(generation+1,next)
+}
+
+implicit val params = LearnerParams("METHINKS IT IS LIKE A WEASEL",0.01,100)
+val initial = (1 to params.target.size) map(x => randchar) mkString
+evolve(0,initial)