Data update
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Ingy döt Net
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858 changed files with 20572 additions and 2082 deletions
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// ------------------------------------- Cross-browser Compatibility -------------------------------------
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/* Compatibility code to reduce an array
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* Source: https://developer.mozilla.org/en/JavaScript/Reference/Global_Objects/Array/Reduce
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*/
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if (!Array.prototype.reduce) {
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Array.prototype.reduce = function (fun /*, initialValue */ ) {
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"use strict";
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if (this === void 0 || this === null) throw new TypeError();
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var t = Object(this);
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var len = t.length >>> 0;
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if (typeof fun !== "function") throw new TypeError();
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// no value to return if no initial value and an empty array
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if (len == 0 && arguments.length == 1) throw new TypeError();
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var k = 0;
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var accumulator;
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if (arguments.length >= 2) {
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accumulator = arguments[1];
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} else {
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do {
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if (k in t) {
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accumulator = t[k++];
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break;
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}
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// if array contains no values, no initial value to return
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if (++k >= len) throw new TypeError();
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}
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while (true);
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}
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while (k < len) {
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if (k in t) accumulator = fun.call(undefined, accumulator, t[k], k, t);
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k++;
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}
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return accumulator;
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};
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}
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/* Compatibility code to map an array
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* Source: https://developer.mozilla.org/en/JavaScript/Reference/Global_Objects/Array/Map
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*/
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if (!Array.prototype.map) {
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Array.prototype.map = function (fun /*, thisp */ ) {
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"use strict";
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if (this === void 0 || this === null) throw new TypeError();
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var t = Object(this);
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var len = t.length >>> 0;
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if (typeof fun !== "function") throw new TypeError();
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var res = new Array(len);
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var thisp = arguments[1];
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for (var i = 0; i < len; i++) {
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if (i in t) res[i] = fun.call(thisp, t[i], i, t);
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}
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return res;
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};
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}
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/* ------------------------------------- Generator -------------------------------------
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* Generates a fixed length gene sequence via a gene strategy object.
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* The gene strategy object must have two functions:
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* - "create": returns create a new gene
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* - "mutate(existingGene)": returns mutation of an existing gene
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*/
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function Generator(length, mutationRate, geneStrategy) {
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this.size = length;
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this.mutationRate = mutationRate;
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this.geneStrategy = geneStrategy;
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}
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Generator.prototype.spawn = function () {
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var genes = [],
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x;
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for (x = 0; x < this.size; x += 1) {
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genes.push(this.geneStrategy.create());
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}
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return genes;
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};
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Generator.prototype.mutate = function (parent) {
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return parent.map(function (char) {
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if (Math.random() > this.mutationRate) {
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return char;
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}
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return this.geneStrategy.mutate(char);
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}, this);
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};
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/* ------------------------------------- Population -------------------------------------
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* Helper class that holds and spawns a new population.
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*/
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function Population(size, generator) {
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this.size = size;
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this.generator = generator;
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this.population = [];
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// Build initial popuation;
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for (var x = 0; x < this.size; x += 1) {
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this.population.push(this.generator.spawn());
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}
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}
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Population.prototype.spawn = function (parent) {
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this.population = [];
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for (var x = 0; x < this.size; x += 1) {
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this.population.push(this.generator.mutate(parent));
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}
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};
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/* ------------------------------------- Evolver -------------------------------------
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* Attempts to converge a population based a fitness strategy object.
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* The fitness strategy object must have three function
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* - "score(individual)": returns a score for an individual.
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* - "compare(scoreA, scoreB)": return true if scoreA is better (ie more fit) then scoreB
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* - "done( score )": return true if score is acceptable (ie we have successfully converged).
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*/
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function Evolver(size, generator, fitness) {
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this.done = false;
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this.fitness = fitness;
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this.population = new Population(size, generator);
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}
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Evolver.prototype.getFittest = function () {
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return this.population.population.reduce(function (best, individual) {
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var currentScore = this.fitness.score(individual);
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if (best === null || this.fitness.compare(currentScore, best.score)) {
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return {
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score: currentScore,
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individual: individual
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};
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} else {
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return best;
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}
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}, null);
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};
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Evolver.prototype.doGeneration = function () {
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this.fittest = this.getFittest();
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this.done = this.fitness.done(this.fittest.score);
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if (!this.done) {
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this.population.spawn(this.fittest.individual);
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}
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};
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Evolver.prototype.run = function (onCheckpoint, checkPointFrequency) {
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checkPointFrequency = checkPointFrequency || 10; // Default to Checkpoints every 10 generations
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var generation = 0;
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while (!this.done) {
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this.doGeneration();
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if (generation % checkPointFrequency === 0) {
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onCheckpoint(generation, this.fittest);
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}
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generation += 1;
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}
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onCheckpoint(generation, this.fittest);
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return this.fittest;
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};
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// ------------------------------------- Exports -------------------------------------
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window.Generator = Generator;
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window.Evolver = Evolver;
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// helper utitlity to combine elements of two arrays.
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Array.prototype.zip = function (b, func) {
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var result = [],
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max = Math.max(this.length, b.length),
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x;
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for (x = 0; x < max; x += 1) {
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result.push(func(this[x], b[x]));
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}
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return result;
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};
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var target = "METHINKS IT IS LIKE A WEASEL", geneStrategy, fitness, target, generator, evolver, result;
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geneStrategy = {
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// The allowed character set (as an array)
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characterSet: "ABCDEFGHIJKLMNOPQRSTUVWXYZ ".split(""),
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/*
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Pick a random character from the characterSet
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*/
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create: function getRandomGene() {
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var randomNumber = Math.floor(Math.random() * this.characterSet.length);
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return this.characterSet[randomNumber];
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}
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};
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geneStrategy.mutate = geneStrategy.create; // Our mutation stragtegy is to simply get a random gene
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fitness = {
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// The target (as an array of characters)
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target: target.split(""),
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equal: function (geneA, geneB) {
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return (geneA === geneB ? 0 : 1);
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},
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sum: function (runningTotal, value) {
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return runningTotal + value;
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},
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/*
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We give one point to for each corect letter
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*/
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score: function (genes) {
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var diff = genes.zip(this.target, this.equal); // create an array of ones and zeros
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return diff.reduce(this.sum, 0); // Sum the array values together.
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},
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compare: function (scoreA, scoreB) {
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return scoreA <= scoreB; // Lower scores are better
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},
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done: function (score) {
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return score === 0; // We have matched the target string.
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}
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};
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generator = new Generator(target.length, 0.05, geneStrategy);
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evolver = new Evolver(100, generator, fitness);
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function showProgress(generation, fittest) {
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document.write("Generation: " + generation + ", Best: " + fittest.individual.join("") + ", fitness:" + fittest.score + "<br>");
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}
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result = evolver.run(showProgress);
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