Modified genetic algorithm to allow survival-rate

package.json

@@ -2,7 +2,7 @@
   "author": "Julian Duniec <julian.duniec@gmail.com>",
   "name": "neural-node",
   "description": "Neural network for NodeJs",
-  "version": "0.0.1",
+  "version": "0.0.2",
   "repository": {
     "type": "git",
     "url": "git://github.com/JulianDuniec/neural-node.git"

src/GeneticAlgorithm.js

@@ -10,6 +10,7 @@
 */
 module.exports = function(options){
 	var me = {};
+	me.survivalRate = options.survivalRate || 0.2;
 	if(!options.sort) {
 		//Default sort-function, sort by fitness descending
 		options.sort = function(a, b) {
@@ -58,18 +59,21 @@ module.exports = function(options){
 		networks.sort(options.sort);
 
 		var len = networks.length;
+
+		var killIndex = Math.floor(me.survivalRate * len);
 
 		//Kill the low-performers
-		networks.splice(2);
+		networks.splice(killIndex);
 
 		//get the parents (first and second )
-		var optionsA = networks[0].export();
-		var optionsB = networks[1].export();
-		var weightsA = optionsA.weights;
-		var weightsB = optionsB.weights;
-		var combined = me.merge(weightsA, weightsB);
+
 		//Add children based on the high-achievers
-		for(var i = 0; i < len-2; i++) {
+		for(var i = 0; i < len-killIndex; i++) {
+			var optionsA = networks[Math.floor(Math.random()*killIndex)].export();
+			var optionsB = networks[Math.floor(Math.random()*killIndex)].export();
+			var weightsA = optionsA.weights;
+			var weightsB = optionsB.weights;
+			var combined = me.merge(weightsA, weightsB);
 			//the same base will be used for every new network, with a unique mutation
 			var mutated = me.mutate(combined);
 			var opts = optionsA;

tests/GeneticAlgorithm.js

@@ -45,16 +45,20 @@ exports.GeneticAlgorithm = {
 		}
 
 		var geneticAlgorithm = new nn.GeneticAlgorithm({
+				survivalRate : 0.5
 
 		});
 
 		networks = geneticAlgorithm.epoch(networks);
 
 		test.equal(networks.length, populationSize);
-		test.ok(networks[0].fitness == 9 );
-		test.ok(networks[1].fitness == 8);
-		for(var i = 2; i < networks.length; i++) {
-			test.ok(networks[i].fitness == null );
+		test.ok(networks[0].fitness == 9, "Fitness incorrect");
+		test.ok(networks[1].fitness == 8, "Fitness incorrect");
+		test.ok(networks[2].fitness == 7, "Fitness incorrect");
+		test.ok(networks[3].fitness == 6, "Fitness incorrect");
+		test.ok(networks[4].fitness == 5, "Fitness incorrect");
+		for(var i = 5; i < networks.length; i++) {
+			test.ok(networks[i].fitness == null, "Fitness was not null");
 		}
 
 		test.done();