findBestGenes.js

/**
* @param {Array} population 
* @param {Number} sampleSize
*/
function randomSample(population, sampleSize) {
  const populationTotal = population.length;
  let result = [];

  while (sampleSize--) {
    const randIndex = Math.floor(Math.random() * populationTotal);
    result.push(population[randIndex]);
  }
  return result;
}

/**
* @param {Number} generations
* Controls how long the experiment will run
*
* @param {Function} mutationFn
* Affects how genes mutate from one generation to the next
*
* @param {Function} getFitnessFn
* Returns the fitness score for a subject's genes
*
* @param {Function} optimalFitnessFn
* Returns the optimal fitness score
*
* @param {Function} displayFn
* Displays progress
*
* @param {Array} geneSet
* The entire superset of possible genes
*
* @param {Number} genesPerSubject
* The number of genes available to individuals in the population
*
* @param {Array|null} genes
* Genes belonging to an individual
*
* @param {Mixed} prevBestFitness
* @param {Mixed} prevBestGenes
*/
function findBestGenes(
  generations = 1000,
  mutationFn,
  getFitnessFn,
  optimalFitnessFn,
  displayFn,
  geneSet,
  genesPerSubject = 100,
  genes = null,
  prevBestFitness = null) {

  // When no generations remain, we've reached the end of the experiment
  if (generations <= 0) {
    return genes;
  }

  // Initialize a random simple on the first call
  if (genes === null) {
    genes = randomSample(geneSet, genesPerSubject);
  }

  let mutatedGenes = mutationFn(genes, geneSet);
  let mutatedFitness = getFitnessFn(mutatedGenes);

  let bestFitness, bestGenes;

  // If the mutated genes outperform the previous
  // genes, designate them as a winner
  if (prevBestFitness === null || mutatedFitness > prevBestFitness) {
    bestFitness = mutatedFitness;
    bestGenes = mutatedGenes;

  // Otherwise, stick with what we have
  } else {
    bestFitness = prevBestFitness;
    bestGenes = genes;
  }

  displayFn(bestGenes, bestFitness);

  // Optimal genes discovered
  if (bestFitness >= optimalFitnessFn()) {
    return genes;
  }

  // TODO: Optimize by implementing this without recursion
  // It's expensive and unnecessary
  const callRecursive = findBestGenes.bind(
    null,
    generations - 1,
    mutationFn,
    getFitnessFn,
    optimalFitnessFn,
    displayFn,
    geneSet,
    genesPerSubject,
    bestGenes,
    bestFitness
  );

  setTimeout(callRecursive, 100);
}