diff --git a/js/genetic-0.1.14.js b/js/genetic-0.1.14.js
index b40a230..3c48e52 100644
--- a/js/genetic-0.1.14.js
+++ b/js/genetic-0.1.14.js
@@ -107,89 +107,173 @@ var Genetic = Genetic || (function(){
 		
 		this.userData = {};
 		this.internalGenState = {};
+		this.callerFunctions = {};
 		
 		this.entities = [];
 		
 		this.usingWebWorker = false;
 		
+		this.mapFitnessAsync = function(entities, callback) {
+			var _this = this;
+
+			var scores = [];
+			var nbScores = 0;
+
+			entities.forEach(function(entity, i) {
+
+				var setScore = function(score) {
+					scores[i] = score;
+					nbScores += 1;
+					if (nbScores === entities.length) {
+						callback(scores);
+					}
+				};
+
+				// Supports fitness function sync or async based on number of expected arguments
+				if (_this.fitness.length === 1) {
+					setScore(_this.fitness(entity));
+				} else {
+					_this.fitness(entity, setScore);
+				}
+			});
+		};
+
+		this.seriesAsync = function(nb, func) {
+			var self = this;
+			var results = [];
+
+			var recursion = function(i) {
+				if(i < nb) {
+					func.call(self, i, function recursionCallback() {
+						recursion(i + 1);
+					});
+				}
+			};
+
+			recursion(0);
+		};
+
 		this.start = function() {
 			
-			var i;
 			var self = this;
 			
+			// prepare wrapping around caller functions
+			for(var k in this.callerFunctions) {
+				this.callerFunctions[k] = this.wrapCallerFunction(k);
+			}
+
 			function mutateOrNot(entity) {
 				// applies mutation based on mutation probability
 				return Math.random() <= self.configuration.mutation && self.mutate ? self.mutate(Clone(entity)) : entity;
 			}
 			
 			// seed the population
-			for (i=0;i<this.configuration.size;++i)  {
+			for (var i=0;i<this.configuration.size;++i)  {
 				this.entities.push(Clone(this.seed()));
 			}
 			
-			for (i=0;i<this.configuration.iterations;++i) {
+			this.seriesAsync(this.configuration.iterations, function runGeneration(i, generationCallback){
 				// reset for each generation
-				this.internalGenState = {};
-				
-				// score and sort
-				var pop = this.entities
-					.map(function (entity) {
-						return {"fitness": self.fitness(entity), "entity": entity };
-					})
-					.sort(function (a, b) {
-						return self.optimize(a.fitness, b.fitness) ? -1 : 1;
-					});
+				self.internalGenState = {};
 				
-				// generation notification
-				var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
-				var stdev = Math.sqrt(pop
-					.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
-					.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+				// Asynchronous score
+				self.mapFitnessAsync(self.entities, function(scores){
+
+					var pop = self.entities
+						.map(function (entity, i) {
+							return {"fitness": scores[i], "entity": entity };
+						})
+						.sort(function (a, b) {
+							return self.optimize(a.fitness, b.fitness) ? -1 : 1;
+						});
 					
-				var stats = {
-					"maximum": pop[0].fitness
-					, "minimum": pop[pop.length-1].fitness
-					, "mean": mean
-					, "stdev": stdev
-				};
+					// generation notification
+					var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
+					var stdev = Math.sqrt(pop
+						.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
+						.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+						
+					var stats = {
+						"maximum": pop[0].fitness
+						, "minimum": pop[pop.length-1].fitness
+						, "mean": mean
+						, "stdev": stdev
+					};
 
-				var r = this.generation ? this.generation(pop, i, stats) : true;
-				var isFinished = (typeof r != "undefined" && !r) || (i == this.configuration.iterations-1);
-				
-				if (
-					this.notification
-					&& (isFinished || this.configuration["skip"] == 0 || i%this.configuration["skip"] == 0)
-				) {
-					this.sendNotification(pop.slice(0, this.maxResults), i, stats, isFinished);
-				}
+					var r = self.generation ? self.generation(pop, i, stats) : true;
+					var isFinished = (typeof r != "undefined" && !r) || (i == self.configuration.iterations-1);
 					
-				if (isFinished)
-					break;
-				
-				// crossover and mutate
-				var newPop = [];
-				
-				if (this.configuration.fittestAlwaysSurvives) // lets the best solution fall through
-					newPop.push(pop[0].entity);
-				
-				while (newPop.length < self.configuration.size) {
 					if (
-						this.crossover // if there is a crossover function
-						&& Math.random() <= this.configuration.crossover // base crossover on specified probability
-						&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						self.notification
+						&& (isFinished || self.configuration["skip"] == 0 || i%self.configuration["skip"] == 0)
 					) {
-						var parents = this.select2(pop);
-						var children = this.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
-						newPop.push(children[0], children[1]);
-					} else {
-						newPop.push(mutateOrNot(self.select1(pop)));
+						self.sendNotification(pop.slice(0, self.maxResults), i, stats, isFinished);
 					}
-				}
-				
-				this.entities = newPop;
-			}
-		}
+						
+					if (isFinished)
+						return;
+					
+					// crossover and mutate
+					var newPop = [];
+					
+					if (self.configuration.fittestAlwaysSurvives) // lets the best solution fall through
+						newPop.push(pop[0].entity);
+					
+					while (newPop.length < self.configuration.size) {
+						if (
+							self.crossover // if there is a crossover function
+							&& Math.random() <= self.configuration.crossover // base crossover on specified probability
+							&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						) {
+							var parents = self.select2(pop);
+							var children = self.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
+							newPop.push(children[0], children[1]);
+						} else {
+							newPop.push(mutateOrNot(self.select1(pop)));
+						}
+					}
+					
+					self.entities = newPop;
+
+					generationCallback();
+				});
+
+			});		
+		};
 		
+		this.callerFunctionsCallbacks = {};
+		this.callbackId = 0;
+		// In the context of a web work a callerFunction is wrapped in a postMessage/onmessage exchange
+		this.wrapCallerFunction = function(funcName) {
+			if (this.usingWebWorker) {
+				// do not use 'self' keyword, here. Weird conflict when in non worker mode
+				var _this = this;
+				return function(){
+					var args = Array.prototype.slice.call(arguments);
+					// This id will be used to create request/reply mechanism
+					_this.callerFunctionsCallbacks[_this.callbackId] = args.pop();
+					postMessage({
+						callerFunction: funcName,
+						id: _this.callbackId,
+						arguments: Serialization.stringify(args)
+					});
+					_this.callbackId += 1;
+				};
+			} else {
+				// self declared outside of scope
+				return self.callerFunctions[funcName];
+			}
+		};
+
+		this.onmessage = function(e) {
+			if (e.data && this.callerFunctionsCallbacks[e.data.id]) {
+				this.callerFunctionsCallbacks[e.data.id].apply(this, Serialization.parse(e.data.arguments));
+				delete this.callerFunctionsCallbacks[e.data.id];
+			} else {
+				this.start();
+			}
+		};
+
 		this.sendNotification = function(pop, generation, stats, isFinished) {
 			var response = {
 				"pop": pop.map(Serialization.stringify)
@@ -209,7 +293,7 @@ var Genetic = Genetic || (function(){
 		};
 	}
 	
-	Genetic.prototype.evolve = function(config, userData) {
+	Genetic.prototype.evolve = function(config, userData, callerFunctions) {
 		
 		var k;
 		for (k in config) {
@@ -219,6 +303,10 @@ var Genetic = Genetic || (function(){
 		for (k in userData) {
 			this.userData[k] = userData[k];
 		}
+
+		for (k in callerFunctions) {
+			this.callerFunctions[k] = callerFunctions[k];
+		}
 		
 		// determine if we can use webworkers
 		this.usingWebWorker = this.configuration.webWorkers
@@ -243,7 +331,7 @@ var Genetic = Genetic || (function(){
 		
 		// materialize our ga instance in the worker
 		blobScript += "var genetic = Serialization.parse(\"" + addslashes(Serialization.stringify(this)) + "\");\n";
-		blobScript += "onmessage = function(e) { genetic.start(); }\n";
+		blobScript += "onmessage = function(e) { genetic.onmessage(e); }\n";
 		
 		var self = this;
 		
@@ -252,19 +340,31 @@ var Genetic = Genetic || (function(){
 			var blob = new Blob([blobScript]);
 			var worker = new Worker(window.URL.createObjectURL(blob));
 			worker.onmessage = function(e) {
-			  var response = e.data;
-			  self.notification(response.pop.map(Serialization.parse), response.generation, response.stats, response.isFinished);
+			  var data = e.data;
+			  if (data.callerFunction) {
+			  	// receive a request from the work to run a function in caller context, do it then respond by postMessage
+			  	self.callerFunctions[data.callerFunction].apply(self, Serialization.parse(data.arguments).concat(function(){
+			  		var args = Array.prototype.slice.call(arguments);
+			  		worker.postMessage({
+			  			callerFunctionCallback: data.callerFunction,
+			  			id: data.id,
+			  			arguments: Serialization.stringify(args)
+			  		});
+			  	}));
+			  } else {
+			  	self.notification(data.pop.map(Serialization.parse), data.generation, data.stats, data.isFinished);
+			  }
 			};
 			worker.onerror = function(e) {
 				alert('ERROR: Line ' + e.lineno + ' in ' + e.filename + ': ' + e.message);
 			};
-			worker.postMessage("");
+			worker.postMessage("start");
 		} else {
 			// simulate webworker
 			(function(){
 				var onmessage;
 				eval(blobScript);
-				onmessage(null);
+				onmessage("start");
 			})();
 		}
 	}
diff --git a/js/genetic-0.1.14.min.js b/js/genetic-0.1.14.min.js
index adec35c..221e043 100644
--- a/js/genetic-0.1.14.min.js
+++ b/js/genetic-0.1.14.min.js
@@ -1 +1 @@
-(function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o<r.length;o++)s(r[o]);return s})({1:[function(require,module,exports){window.Genetic=require("./genetic")},{"./genetic":2}],2:[function(require,module,exports){var Genetic=Genetic||function(){"use strict";var Serialization={stringify:function(obj){return JSON.stringify(obj,function(key,value){if(value instanceof Function||typeof value=="function")return"__func__:"+value.toString();if(value instanceof RegExp)return"__regex__:"+value;return value})},parse:function(str){return JSON.parse(str,function(key,value){if(typeof value!="string")return value;if(value.lastIndexOf("__func__:",0)===0)return eval("("+value.slice(9)+")");if(value.lastIndexOf("__regex__:",0)===0)return eval("("+value.slice(10)+")");return value})}};var Clone=function(obj){if(obj==null||typeof obj!="object")return obj;return JSON.parse(JSON.stringify(obj))};var Optimize={Maximize:function(a,b){return a>=b},Minimize:function(a,b){return a<b}};var Select1={Tournament2:function(pop){var n=pop.length;var a=pop[Math.floor(Math.random()*n)];var b=pop[Math.floor(Math.random()*n)];return this.optimize(a.fitness,b.fitness)?a.entity:b.entity},Tournament3:function(pop){var n=pop.length;var a=pop[Math.floor(Math.random()*n)];var b=pop[Math.floor(Math.random()*n)];var c=pop[Math.floor(Math.random()*n)];var best=this.optimize(a.fitness,b.fitness)?a:b;best=this.optimize(best.fitness,c.fitness)?best:c;return best.entity},Fittest:function(pop){return pop[0].entity},Random:function(pop){return pop[Math.floor(Math.random()*pop.length)].entity},RandomLinearRank:function(pop){this.internalGenState["rlr"]=this.internalGenState["rlr"]||0;return pop[Math.floor(Math.random()*Math.min(pop.length,this.internalGenState["rlr"]++))].entity},Sequential:function(pop){this.internalGenState["seq"]=this.internalGenState["seq"]||0;return pop[this.internalGenState["seq"]++%pop.length].entity}};var Select2={Tournament2:function(pop){return[Select1.Tournament2.call(this,pop),Select1.Tournament2.call(this,pop)]},Tournament3:function(pop){return[Select1.Tournament3.call(this,pop),Select1.Tournament3.call(this,pop)]},Random:function(pop){return[Select1.Random.call(this,pop),Select1.Random.call(this,pop)]},RandomLinearRank:function(pop){return[Select1.RandomLinearRank.call(this,pop),Select1.RandomLinearRank.call(this,pop)]},Sequential:function(pop){return[Select1.Sequential.call(this,pop),Select1.Sequential.call(this,pop)]},FittestRandom:function(pop){return[Select1.Fittest.call(this,pop),Select1.Random.call(this,pop)]}};function Genetic(){this.fitness=null;this.seed=null;this.mutate=null;this.crossover=null;this.select1=null;this.select2=null;this.optimize=null;this.generation=null;this.notification=null;this.configuration={size:250,crossover:.9,mutation:.2,iterations:100,fittestAlwaysSurvives:true,maxResults:100,webWorkers:true,skip:0};this.userData={};this.internalGenState={};this.entities=[];this.usingWebWorker=false;this.start=function(){var i;var self=this;function mutateOrNot(entity){return Math.random()<=self.configuration.mutation&&self.mutate?self.mutate(Clone(entity)):entity}for(i=0;i<this.configuration.size;++i){this.entities.push(Clone(this.seed()))}for(i=0;i<this.configuration.iterations;++i){this.internalGenState={};var pop=this.entities.map(function(entity){return{fitness:self.fitness(entity),entity:entity}}).sort(function(a,b){return self.optimize(a.fitness,b.fitness)?-1:1});var mean=pop.reduce(function(a,b){return a+b.fitness},0)/pop.length;var stdev=Math.sqrt(pop.map(function(a){return(a.fitness-mean)*(a.fitness-mean)}).reduce(function(a,b){return a+b},0)/pop.length);var stats={maximum:pop[0].fitness,minimum:pop[pop.length-1].fitness,mean:mean,stdev:stdev};var r=this.generation?this.generation(pop,i,stats):true;var isFinished=typeof r!="undefined"&&!r||i==this.configuration.iterations-1;if(this.notification&&(isFinished||this.configuration["skip"]==0||i%this.configuration["skip"]==0)){this.sendNotification(pop.slice(0,this.maxResults),i,stats,isFinished)}if(isFinished)break;var newPop=[];if(this.configuration.fittestAlwaysSurvives)newPop.push(pop[0].entity);while(newPop.length<self.configuration.size){if(this.crossover&&Math.random()<=this.configuration.crossover&&newPop.length+1<self.configuration.size){var parents=this.select2(pop);var children=this.crossover(Clone(parents[0]),Clone(parents[1])).map(mutateOrNot);newPop.push(children[0],children[1])}else{newPop.push(mutateOrNot(self.select1(pop)))}}this.entities=newPop}};this.sendNotification=function(pop,generation,stats,isFinished){var response={pop:pop.map(Serialization.stringify),generation:generation,stats:stats,isFinished:isFinished};if(this.usingWebWorker){postMessage(response)}else{self.notification(response.pop.map(Serialization.parse),response.generation,response.stats,response.isFinished)}}}Genetic.prototype.evolve=function(config,userData){var k;for(k in config){this.configuration[k]=config[k]}for(k in userData){this.userData[k]=userData[k]}this.usingWebWorker=this.configuration.webWorkers&&typeof Blob!="undefined"&&typeof Worker!="undefined"&&typeof window.URL!="undefined"&&typeof window.URL.createObjectURL!="undefined";function addslashes(str){return str.replace(/[\\"']/g,"\\$&").replace(/\u0000/g,"\\0")}var blobScript="'use strict'\n";blobScript+="var Serialization = {'stringify': "+Serialization.stringify.toString()+", 'parse': "+Serialization.parse.toString()+"};\n";blobScript+="var Clone = "+Clone.toString()+";\n";blobScript+='var Optimize = Serialization.parse("'+addslashes(Serialization.stringify(Optimize))+'");\n';blobScript+='var Select1 = Serialization.parse("'+addslashes(Serialization.stringify(Select1))+'");\n';blobScript+='var Select2 = Serialization.parse("'+addslashes(Serialization.stringify(Select2))+'");\n';blobScript+='var genetic = Serialization.parse("'+addslashes(Serialization.stringify(this))+'");\n';blobScript+="onmessage = function(e) { genetic.start(); }\n";var self=this;if(this.usingWebWorker){var blob=new Blob([blobScript]);var worker=new Worker(window.URL.createObjectURL(blob));worker.onmessage=function(e){var response=e.data;self.notification(response.pop.map(Serialization.parse),response.generation,response.stats,response.isFinished)};worker.onerror=function(e){alert("ERROR: Line "+e.lineno+" in "+e.filename+": "+e.message)};worker.postMessage("")}else{(function(){var onmessage;eval(blobScript);onmessage(null)})()}};return{create:function(){return new Genetic},Select1:Select1,Select2:Select2,Optimize:Optimize,Clone:Clone}}();if(typeof module!="undefined"){module.exports=Genetic}},{}]},{},[1]);
\ No newline at end of file
+(function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o<r.length;o++)s(r[o]);return s})({1:[function(require,module,exports){window.Genetic=require("./genetic")},{"./genetic":2}],2:[function(require,module,exports){var Genetic=Genetic||function(){"use strict";var Serialization={stringify:function(obj){return JSON.stringify(obj,function(key,value){if(value instanceof Function||typeof value=="function")return"__func__:"+value.toString();if(value instanceof RegExp)return"__regex__:"+value;return value})},parse:function(str){return JSON.parse(str,function(key,value){if(typeof value!="string")return value;if(value.lastIndexOf("__func__:",0)===0)return eval("("+value.slice(9)+")");if(value.lastIndexOf("__regex__:",0)===0)return eval("("+value.slice(10)+")");return value})}};var Clone=function(obj){if(obj==null||typeof obj!="object")return obj;return JSON.parse(JSON.stringify(obj))};var Optimize={Maximize:function(a,b){return a>=b},Minimize:function(a,b){return a<b}};var Select1={Tournament2:function(pop){var n=pop.length;var a=pop[Math.floor(Math.random()*n)];var b=pop[Math.floor(Math.random()*n)];return this.optimize(a.fitness,b.fitness)?a.entity:b.entity},Tournament3:function(pop){var n=pop.length;var a=pop[Math.floor(Math.random()*n)];var b=pop[Math.floor(Math.random()*n)];var c=pop[Math.floor(Math.random()*n)];var best=this.optimize(a.fitness,b.fitness)?a:b;best=this.optimize(best.fitness,c.fitness)?best:c;return best.entity},Fittest:function(pop){return pop[0].entity},Random:function(pop){return pop[Math.floor(Math.random()*pop.length)].entity},RandomLinearRank:function(pop){this.internalGenState["rlr"]=this.internalGenState["rlr"]||0;return pop[Math.floor(Math.random()*Math.min(pop.length,this.internalGenState["rlr"]++))].entity},Sequential:function(pop){this.internalGenState["seq"]=this.internalGenState["seq"]||0;return pop[this.internalGenState["seq"]++%pop.length].entity}};var Select2={Tournament2:function(pop){return[Select1.Tournament2.call(this,pop),Select1.Tournament2.call(this,pop)]},Tournament3:function(pop){return[Select1.Tournament3.call(this,pop),Select1.Tournament3.call(this,pop)]},Random:function(pop){return[Select1.Random.call(this,pop),Select1.Random.call(this,pop)]},RandomLinearRank:function(pop){return[Select1.RandomLinearRank.call(this,pop),Select1.RandomLinearRank.call(this,pop)]},Sequential:function(pop){return[Select1.Sequential.call(this,pop),Select1.Sequential.call(this,pop)]},FittestRandom:function(pop){return[Select1.Fittest.call(this,pop),Select1.Random.call(this,pop)]}};function Genetic(){this.fitness=null;this.seed=null;this.mutate=null;this.crossover=null;this.select1=null;this.select2=null;this.optimize=null;this.generation=null;this.notification=null;this.configuration={size:250,crossover:.9,mutation:.2,iterations:100,fittestAlwaysSurvives:true,maxResults:100,webWorkers:true,skip:0};this.userData={};this.internalGenState={};this.callerFunctions={};this.entities=[];this.usingWebWorker=false;this.mapFitnessAsync=function(entities,callback){var _this=this;var scores=[];var nbScores=0;entities.forEach(function(entity,i){var setScore=function(score){scores[i]=score;nbScores+=1;if(nbScores===entities.length){callback(scores)}};if(_this.fitness.length===1){setScore(_this.fitness(entity))}else{_this.fitness(entity,setScore)}})};this.seriesAsync=function(nb,func){var self=this;var results=[];var recursion=function(i){if(i<nb){func.call(self,i,function recursionCallback(){recursion(i+1)})}};recursion(0)};this.start=function(){var self=this;for(var k in this.callerFunctions){this.callerFunctions[k]=this.wrapCallerFunction(k)}function mutateOrNot(entity){return Math.random()<=self.configuration.mutation&&self.mutate?self.mutate(Clone(entity)):entity}for(var i=0;i<this.configuration.size;++i){this.entities.push(Clone(this.seed()))}this.seriesAsync(this.configuration.iterations,function runGeneration(i,generationCallback){self.internalGenState={};self.mapFitnessAsync(self.entities,function(scores){var pop=self.entities.map(function(entity,i){return{fitness:scores[i],entity:entity}}).sort(function(a,b){return self.optimize(a.fitness,b.fitness)?-1:1});var mean=pop.reduce(function(a,b){return a+b.fitness},0)/pop.length;var stdev=Math.sqrt(pop.map(function(a){return(a.fitness-mean)*(a.fitness-mean)}).reduce(function(a,b){return a+b},0)/pop.length);var stats={maximum:pop[0].fitness,minimum:pop[pop.length-1].fitness,mean:mean,stdev:stdev};var r=self.generation?self.generation(pop,i,stats):true;var isFinished=typeof r!="undefined"&&!r||i==self.configuration.iterations-1;if(self.notification&&(isFinished||self.configuration["skip"]==0||i%self.configuration["skip"]==0)){self.sendNotification(pop.slice(0,self.maxResults),i,stats,isFinished)}if(isFinished)return;var newPop=[];if(self.configuration.fittestAlwaysSurvives)newPop.push(pop[0].entity);while(newPop.length<self.configuration.size){if(self.crossover&&Math.random()<=self.configuration.crossover&&newPop.length+1<self.configuration.size){var parents=self.select2(pop);var children=self.crossover(Clone(parents[0]),Clone(parents[1])).map(mutateOrNot);newPop.push(children[0],children[1])}else{newPop.push(mutateOrNot(self.select1(pop)))}}self.entities=newPop;generationCallback()})})};this.callerFunctionsCallbacks={};this.callbackId=0;this.wrapCallerFunction=function(funcName){if(this.usingWebWorker){var _this=this;return function(){var args=Array.prototype.slice.call(arguments);_this.callerFunctionsCallbacks[_this.callbackId]=args.pop();postMessage({callerFunction:funcName,id:_this.callbackId,arguments:Serialization.stringify(args)});_this.callbackId+=1}}else{return self.callerFunctions[funcName]}};this.onmessage=function(e){if(e.data&&this.callerFunctionsCallbacks[e.data.id]){this.callerFunctionsCallbacks[e.data.id].apply(this,Serialization.parse(e.data.arguments));delete this.callerFunctionsCallbacks[e.data.id]}else{this.start()}};this.sendNotification=function(pop,generation,stats,isFinished){var response={pop:pop.map(Serialization.stringify),generation:generation,stats:stats,isFinished:isFinished};if(this.usingWebWorker){postMessage(response)}else{self.notification(response.pop.map(Serialization.parse),response.generation,response.stats,response.isFinished)}}}Genetic.prototype.evolve=function(config,userData,callerFunctions){var k;for(k in config){this.configuration[k]=config[k]}for(k in userData){this.userData[k]=userData[k]}for(k in callerFunctions){this.callerFunctions[k]=callerFunctions[k]}this.usingWebWorker=this.configuration.webWorkers&&typeof Blob!="undefined"&&typeof Worker!="undefined"&&typeof window.URL!="undefined"&&typeof window.URL.createObjectURL!="undefined";function addslashes(str){return str.replace(/[\\"']/g,"\\$&").replace(/\u0000/g,"\\0")}var blobScript="'use strict'\n";blobScript+="var Serialization = {'stringify': "+Serialization.stringify.toString()+", 'parse': "+Serialization.parse.toString()+"};\n";blobScript+="var Clone = "+Clone.toString()+";\n";blobScript+='var Optimize = Serialization.parse("'+addslashes(Serialization.stringify(Optimize))+'");\n';blobScript+='var Select1 = Serialization.parse("'+addslashes(Serialization.stringify(Select1))+'");\n';blobScript+='var Select2 = Serialization.parse("'+addslashes(Serialization.stringify(Select2))+'");\n';blobScript+='var genetic = Serialization.parse("'+addslashes(Serialization.stringify(this))+'");\n';blobScript+="onmessage = function(e) { genetic.onmessage(e); }\n";var self=this;if(this.usingWebWorker){var blob=new Blob([blobScript]);var worker=new Worker(window.URL.createObjectURL(blob));worker.onmessage=function(e){var data=e.data;if(data.callerFunction){self.callerFunctions[data.callerFunction].apply(self,Serialization.parse(data.arguments).concat(function(){var args=Array.prototype.slice.call(arguments);worker.postMessage({callerFunctionCallback:data.callerFunction,id:data.id,arguments:Serialization.stringify(args)})}))}else{self.notification(data.pop.map(Serialization.parse),data.generation,data.stats,data.isFinished)}};worker.onerror=function(e){alert("ERROR: Line "+e.lineno+" in "+e.filename+": "+e.message)};worker.postMessage("start")}else{(function(){var onmessage;eval(blobScript);onmessage("start")})()}};return{create:function(){return new Genetic},Select1:Select1,Select2:Select2,Optimize:Optimize,Clone:Clone}}();if(typeof module!="undefined"){module.exports=Genetic}},{}]},{},[1]);
diff --git a/lib/genetic.js b/lib/genetic.js
index 7564024..019a85c 100644
--- a/lib/genetic.js
+++ b/lib/genetic.js
@@ -102,89 +102,173 @@ var Genetic = Genetic || (function(){
 		
 		this.userData = {};
 		this.internalGenState = {};
+		this.callerFunctions = {};
 		
 		this.entities = [];
 		
 		this.usingWebWorker = false;
 		
+		this.mapFitnessAsync = function(entities, callback) {
+			var _this = this;
+
+			var scores = [];
+			var nbScores = 0;
+
+			entities.forEach(function(entity, i) {
+
+				var setScore = function(score) {
+					scores[i] = score;
+					nbScores += 1;
+					if (nbScores === entities.length) {
+						callback(scores);
+					}
+				};
+
+				// Supports fitness function sync or async based on number of expected arguments
+				if (_this.fitness.length === 1) {
+					setScore(_this.fitness(entity));
+				} else {
+					_this.fitness(entity, setScore);
+				}
+			});
+		};
+
+		this.seriesAsync = function(nb, func) {
+			var self = this;
+			var results = [];
+
+			var recursion = function(i) {
+				if(i < nb) {
+					func.call(self, i, function recursionCallback() {
+						recursion(i + 1);
+					});
+				}
+			};
+
+			recursion(0);
+		};
+
 		this.start = function() {
 			
-			var i;
 			var self = this;
 			
+			// prepare wrapping around caller functions
+			for(var k in this.callerFunctions) {
+				this.callerFunctions[k] = this.wrapCallerFunction(k);
+			}
+
 			function mutateOrNot(entity) {
 				// applies mutation based on mutation probability
 				return Math.random() <= self.configuration.mutation && self.mutate ? self.mutate(Clone(entity)) : entity;
 			}
 			
 			// seed the population
-			for (i=0;i<this.configuration.size;++i)  {
+			for (var i=0;i<this.configuration.size;++i)  {
 				this.entities.push(Clone(this.seed()));
 			}
 			
-			for (i=0;i<this.configuration.iterations;++i) {
+			this.seriesAsync(this.configuration.iterations, function runGeneration(i, generationCallback){
 				// reset for each generation
-				this.internalGenState = {};
-				
-				// score and sort
-				var pop = this.entities
-					.map(function (entity) {
-						return {"fitness": self.fitness(entity), "entity": entity };
-					})
-					.sort(function (a, b) {
-						return self.optimize(a.fitness, b.fitness) ? -1 : 1;
-					});
+				self.internalGenState = {};
 				
-				// generation notification
-				var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
-				var stdev = Math.sqrt(pop
-					.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
-					.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+				// Asynchronous score
+				self.mapFitnessAsync(self.entities, function(scores){
+
+					var pop = self.entities
+						.map(function (entity, i) {
+							return {"fitness": scores[i], "entity": entity };
+						})
+						.sort(function (a, b) {
+							return self.optimize(a.fitness, b.fitness) ? -1 : 1;
+						});
 					
-				var stats = {
-					"maximum": pop[0].fitness
-					, "minimum": pop[pop.length-1].fitness
-					, "mean": mean
-					, "stdev": stdev
-				};
+					// generation notification
+					var mean = pop.reduce(function (a, b) { return a + b.fitness; }, 0)/pop.length;
+					var stdev = Math.sqrt(pop
+						.map(function (a) { return (a.fitness - mean) * (a.fitness - mean); })
+						.reduce(function (a, b) { return a+b; }, 0)/pop.length);
+						
+					var stats = {
+						"maximum": pop[0].fitness
+						, "minimum": pop[pop.length-1].fitness
+						, "mean": mean
+						, "stdev": stdev
+					};
 
-				var r = this.generation ? this.generation(pop, i, stats) : true;
-				var isFinished = (typeof r != "undefined" && !r) || (i == this.configuration.iterations-1);
-				
-				if (
-					this.notification
-					&& (isFinished || this.configuration["skip"] == 0 || i%this.configuration["skip"] == 0)
-				) {
-					this.sendNotification(pop.slice(0, this.maxResults), i, stats, isFinished);
-				}
+					var r = self.generation ? self.generation(pop, i, stats) : true;
+					var isFinished = (typeof r != "undefined" && !r) || (i == self.configuration.iterations-1);
 					
-				if (isFinished)
-					break;
-				
-				// crossover and mutate
-				var newPop = [];
-				
-				if (this.configuration.fittestAlwaysSurvives) // lets the best solution fall through
-					newPop.push(pop[0].entity);
-				
-				while (newPop.length < self.configuration.size) {
 					if (
-						this.crossover // if there is a crossover function
-						&& Math.random() <= this.configuration.crossover // base crossover on specified probability
-						&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						self.notification
+						&& (isFinished || self.configuration["skip"] == 0 || i%self.configuration["skip"] == 0)
 					) {
-						var parents = this.select2(pop);
-						var children = this.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
-						newPop.push(children[0], children[1]);
-					} else {
-						newPop.push(mutateOrNot(self.select1(pop)));
+						self.sendNotification(pop.slice(0, self.maxResults), i, stats, isFinished);
 					}
-				}
-				
-				this.entities = newPop;
-			}
-		}
+						
+					if (isFinished)
+						return;
+					
+					// crossover and mutate
+					var newPop = [];
+					
+					if (self.configuration.fittestAlwaysSurvives) // lets the best solution fall through
+						newPop.push(pop[0].entity);
+					
+					while (newPop.length < self.configuration.size) {
+						if (
+							self.crossover // if there is a crossover function
+							&& Math.random() <= self.configuration.crossover // base crossover on specified probability
+							&& newPop.length+1 < self.configuration.size // keeps us from going 1 over the max population size
+						) {
+							var parents = self.select2(pop);
+							var children = self.crossover(Clone(parents[0]), Clone(parents[1])).map(mutateOrNot);
+							newPop.push(children[0], children[1]);
+						} else {
+							newPop.push(mutateOrNot(self.select1(pop)));
+						}
+					}
+					
+					self.entities = newPop;
+
+					generationCallback();
+				});
+
+			});		
+		};
 		
+		this.callerFunctionsCallbacks = {};
+		this.callbackId = 0;
+		// In the context of a web work a callerFunction is wrapped in a postMessage/onmessage exchange
+		this.wrapCallerFunction = function(funcName) {
+			if (this.usingWebWorker) {
+				// do not use 'self' keyword, here. Weird conflict when in non worker mode
+				var _this = this;
+				return function(){
+					var args = Array.prototype.slice.call(arguments);
+					// This id will be used to create request/reply mechanism
+					_this.callerFunctionsCallbacks[_this.callbackId] = args.pop();
+					postMessage({
+						callerFunction: funcName,
+						id: _this.callbackId,
+						arguments: args
+					});
+					_this.callbackId += 1;
+				};
+			} else {
+				// self declared outside of scope
+				return self.callerFunctions[funcName];
+			}
+		};
+
+		this.onmessage = function(e) {
+			if (e.data && this.callerFunctionsCallbacks[e.data.id]) {
+				this.callerFunctionsCallbacks[e.data.id].apply(this, e.data.arguments);
+				delete this.callerFunctionsCallbacks[e.data.id];
+			} else {
+				this.start();
+			}
+		};
+
 		this.sendNotification = function(pop, generation, stats, isFinished) {
 			var response = {
 				"pop": pop.map(Serialization.stringify)
@@ -204,7 +288,7 @@ var Genetic = Genetic || (function(){
 		};
 	}
 	
-	Genetic.prototype.evolve = function(config, userData) {
+	Genetic.prototype.evolve = function(config, userData, callerFunctions) {
 		
 		var k;
 		for (k in config) {
@@ -214,6 +298,10 @@ var Genetic = Genetic || (function(){
 		for (k in userData) {
 			this.userData[k] = userData[k];
 		}
+
+		for (k in callerFunctions) {
+			this.callerFunctions[k] = callerFunctions[k];
+		}
 		
 		// determine if we can use webworkers
 		this.usingWebWorker = this.configuration.webWorkers
@@ -238,28 +326,41 @@ var Genetic = Genetic || (function(){
 		
 		// materialize our ga instance in the worker
 		blobScript += "var genetic = Serialization.parse(\"" + addslashes(Serialization.stringify(this)) + "\");\n";
-		blobScript += "onmessage = function(e) { genetic.start(); }\n";
+		blobScript += "onmessage = function(e) { genetic.onmessage(e); }\n";
 		
 		var self = this;
 		
 		if (this.usingWebWorker) {
 			// webworker
+
 			var blob = new Blob([blobScript]);
 			var worker = new Worker(window.URL.createObjectURL(blob));
 			worker.onmessage = function(e) {
-			  var response = e.data;
-			  self.notification(response.pop.map(Serialization.parse), response.generation, response.stats, response.isFinished);
+			  var data = e.data;
+			  if (data.callerFunction) {
+			  	// receive a request from the work to run a function in caller context, do it then respond by postMessage
+			  	self.callerFunctions[data.callerFunction].apply(self, data.arguments.concat(function(){
+			  		var args = Array.prototype.slice.call(arguments);
+			  		worker.postMessage({
+			  			callerFunctionCallback: data.callerFunction,
+			  			id: data.id,
+			  			arguments: args
+			  		});
+			  	}));
+			  } else {
+			  	self.notification(data.pop.map(Serialization.parse), data.generation, data.stats, data.isFinished);
+			  }
 			};
 			worker.onerror = function(e) {
 				alert('ERROR: Line ' + e.lineno + ' in ' + e.filename + ': ' + e.message);
 			};
-			worker.postMessage("");
+			worker.postMessage("start");
 		} else {
 			// simulate webworker
 			(function(){
 				var onmessage;
 				eval(blobScript);
-				onmessage(null);
+				onmessage("start");
 			})();
 		}
 	}
diff --git a/test/async.js b/test/async.js
new file mode 100644
index 0000000..d881290
--- /dev/null
+++ b/test/async.js
@@ -0,0 +1,92 @@
+
+if (typeof require === 'function') {
+	var Genetic = require("../lib/genetic");
+	var assert = require("assert");
+}
+
+
+var genetic;
+
+beforeEach(function () {
+	genetic = Genetic.create();
+});
+
+
+describe("Async", function() {
+	it("fitness", function (done) {
+		genetic.optimize = Genetic.Optimize.Maximize;
+		genetic.select1 = Genetic.Select1.Tournament2;
+		genetic.seed = function() {
+			return 0;
+		};
+		genetic.mutate = function(entity) {
+			return entity;
+		};
+
+		genetic.fitness = function(entity, callback) {
+			this.internalGenState.val = this.internalGenState.val || 0;
+			this.internalGenState.val += 1;
+			var val = this.internalGenState.val;
+			setTimeout(function(){
+				callback(val);
+			}, 1);
+		};
+		
+		var count = 0;
+		genetic.notification = function(pop, generation, stats, isFinished) {
+			count++;
+			if (isFinished) {
+				assert.equal(count, 2);
+				assert.equal(stats.maximum, 10);
+				assert.equal(stats.mean, 5.5);
+				done();
+			}
+		};
+		var config = {
+			"iterations": 2
+			, "size": 10
+			, "crossover": 0.0
+			, "skip": 10
+		};
+		genetic.evolve(config);
+	});
+
+	it("caller function", function (done) {
+		genetic.optimize = Genetic.Optimize.Maximize;
+		genetic.select1 = Genetic.Select1.Tournament2;
+		genetic.seed = function() {
+			return 0;
+		};
+		genetic.mutate = function(entity) {
+			return entity;
+		};
+
+		genetic.fitness = function(entity, callback) {
+			this.callerFunctions.getCallerVar(callback);
+		};
+		
+		var count = 0;
+		genetic.notification = function(pop, generation, stats, isFinished) {
+			if (isFinished) {
+				assert.equal(stats.maximum, 10);
+				assert.equal(stats.mean, 5.5);
+				done();
+			}
+		};
+		var config = {
+			"iterations": 1
+			, "size": 10
+			, "crossover": 0.0
+			, "skip": 1
+		};
+
+		var callerVar = 0;
+
+		genetic.evolve(config, {}, {
+			getCallerVar: function(callback){
+				callerVar += 1;
+				callback(callerVar);
+			}
+		});
+	});
+});
\ No newline at end of file
diff --git a/test/index.html b/test/index.html
new file mode 100644
index 0000000..a8198de
--- /dev/null
+++ b/test/index.html
@@ -0,0 +1,25 @@
+<html>
+<head>
+  <meta charset="utf-8">
+  <title>Mocha Tests</title>
+  <link href="https://cdn.rawgit.com/mochajs/mocha/2.2.5/mocha.css" rel="stylesheet" />
+</head>
+<body>
+  <div id="mocha"></div>
+
+  <script src="../js/genetic-0.1.14.js"></script>
+  <script src="https://rawgit.com/Jxck/assert/master/assert.js"></script>
+  <script src="https://cdn.rawgit.com/mochajs/mocha/2.2.5/mocha.js"></script>
+
+  <script>mocha.setup('bdd')</script>
+  <script src="async.js"></script>
+  <script src="config.js"></script>
+  <script src="misc.js"></script>
+  <script src="parabolic.js"></script>
+  <script src="string.js"></script>
+  <script>
+    mocha.checkLeaks();
+    mocha.run();
+  </script>
+</body>
+</html>
\ No newline at end of file