Finished (solo falta documentación)

Tetris AI/src/AI.cpp

@@ -3,6 +3,7 @@
 //  Tetris AI
 //
 //  Created by Roberto Ariosa Hernández on 09/01/2018.
+//  Copyright © 2018 Mr.Robb. All rights reserved.
 //
 
 #include "AI.hpp"

Tetris AI/src/AI.hpp

@@ -3,6 +3,7 @@
 //  Tetris AI
 //
 //  Created by Roberto Ariosa Hernández on 09/01/2018.
+//  Copyright © 2018 Mr.Robb. All rights reserved.
 //
 
 #ifndef AI_hpp
@@ -26,10 +27,10 @@ struct Shape {
 };
 
 class AI {
-	float aggregate_height = -3.78;
-	float complete_lines = 1.6;
-	float holes = -2.31;
-	float bumpiness = -0.59;
+	float aggregate_height = 0.132802;
+	float complete_lines = 0.132802;
+	float holes = -0.344799;
+	float bumpiness = -0.0387222;
 
 	vector< vector<unsigned char> > grid;
 	map<int,vector< vector<unsigned char> > > shapes;

Tetris AI/src/DNA.hpp

@@ -40,6 +40,7 @@ class DNA {
 	 @brief Access the genes directly.
 	 @pre i must be between 0 and lenght-1.
 	 @param i Position of the gene.
+	 @return The gene at position i.
 	 */
 	float& operator[](int i);
 
@@ -60,6 +61,7 @@ class DNA {
 	/**
 	 @brief Get the fitness of the individual.
 	 @pre Fitness function has been already executed.
+	 @return The fitness of the individual.
 	 @see DNA::fitness
 	 */
 	float getFitness();
@@ -68,6 +70,7 @@ class DNA {
 	 @brief Creates a child with mixed genes via crossover.
 	 @f$ itself + partner = child @f$
 	 @param partner It will provide some genetic information.
+	 @return The child.
 	 */
 	DNA crossover(DNA &partner);
 

Tetris AI/src/Population.cpp

@@ -8,104 +8,119 @@
 
 #include "Population.hpp"
 
-Population::Population() {
-
-}
+Population::Population() {}
 
-// construct
-Population::Population(int length, float mutationRate, int N_ind, int generation) {
+Population::Population(int N_genes, int N_ind, float mutationRate, unsigned int generation)
+{
 	this->mutationRate = mutationRate;
 	this->generation = generation;
 	pool = vector<DNA> ();
 	population = vector<DNA> (N_ind, DNA());
-	for (int i = 0; i < N_ind; i++) {
-		population[i] = DNA(length);
-	}
+
+	for (int i = 0; i < N_ind; i++)
+		population[i] = DNA(N_genes);
 }
 
-DNA Population::operator[](int i) {
+DNA& Population::operator[](int i)
+{
 	return this->population[i];
 }
 
-// call fitness for every specimen
-void Population::calculateFitness(vector<int> scores) {
+void Population::calculateFitness(vector<int> scores)
+{
 	int max_score = *max_element(scores.begin(), scores.end());
-	for (int i = 0; i < population.size(); i++) {
+
+	// Call fitness() for every Individual
+	for (int i = 0; i < population.size(); i++)
 		population[i].fitness(scores[i], max_score);
-	}
 }
 
-// reproduce
-void Population::naturalSelection() {
-	int i = getBest();
-	float maxFitness = population[i].getFitness();
-
-	for (int i = 0; i < population.size(); i++) {
-		float relative_fitness = population[i].getFitness() / maxFitness;
-		int percentage = int(relative_fitness * 100);
-		for (int j = 0; j < percentage; j++) {
-			pool.push_back(population[i]);
-		}
-	}
-}
-
-// create new generation
-Population Population::generate(int length) {
-	Population p (length, mutationRate, int(population.size()), generation + 1);
-	if (pool.size() > 0) {
+Population Population::generate()
+{
+	// Fill the temporary reproduction pool
+	naturalSelection();
+
+	// Create container of the next generation
+	int N_ind = int(population.size());
+	int N_genes = int(population[0].getValues().size());
+	Population p (N_genes, N_ind, mutationRate, generation + 1);
+
+	// Fill pool
+	if (pool.size() > 0)
+	{
 		for (int i = 0; i < population.size(); i++) {
 			int a = int(rand() % pool.size());
 			int b = int(rand() % pool.size());
 			DNA dna_a = this->pool[a];
 			DNA dna_b = this->pool[b];
 			DNA child = dna_a.crossover(dna_b);
-			child.mutate(mutationRate, generation+1);
+			child.mutate(mutationRate);
 			p.population[i] = child;
 		}
+
+		// Free pool
 		pool = vector<DNA>();
 	}
+
 	return p;
 }
 
-// most fit
-int Population::getBest() {
+int Population::getBest()
+{
 	float record = 0.0;
 	int index = 0;
-	for (int i = 0; i < population.size(); i++) {
-		if (population[i].getFitness() > record) {
+
+	for (int i = 0; i < population.size(); i++)
+	{
+		float current = population[i].getFitness();
+
+		if (current > record) {
 			index = i;
-
-			record = population[i].getFitness();
+			record = current;
 		}
 	}
+
 	return index;
 }
 
-// finished
-bool Population::isFinished() {
-	finished = (population[getBest()].getFitness() == perfectScore);
-	return finished;
-}
-
-int Population::getGenerations() {
+int Population::getGenerations()
+{
 	return generation;
 }
 
-float Population::getAverage() {
+float Population::getAverage()
+{
 	float total = 0.0;
-	for (int i = 0; i < population.size(); i++) {
+
+	for (int i = 0; i < population.size(); i++)
 		total += population[i].getFitness();
-	}
+
 	return total / (float) population.size();
 }
 
-vector< vector<float> > Population::allValues() {
-	vector< vector<float> > all (population.size(), vector<float> (4));
-	for (int i = 0; i < population.size(); i++) {
-		for (int j = 0; j < 4; j++) {
+vector< vector<float> > Population::allValues()
+{
+	int N_ind = int(population.size());
+	int N_genes = int(population[0].getValues().size());
+	vector< vector<float> > all (N_ind, vector<float> (N_genes));
+
+	for (int i = 0; i < N_ind; i++) {
+		for (int j = 0; j < N_genes; j++) {
 			all[i][j] = population[i][j];
 		}
 	}
+
 	return all;
 }
 
+void Population::naturalSelection()
+{
+	for (int i = 0; i < population.size(); i++)
+	{
+		float fitness = population[i].getFitness();
+		int percentage = int(fitness * 100);
+
+		for (int j = 0; j < percentage; j++)
+			pool.push_back(population[i]);
+	}
+}

Tetris AI/src/Population.hpp

@@ -17,43 +17,87 @@
 using namespace std;
 
 class Population {
-private:
-	float mutationRate;
-	vector<DNA> population;
-	vector<DNA> pool;
-	string target;
-	int generation;
-	bool finished;
-	int perfectScore;
 
 public:
+	/**
+	 @brief Creates an empty Population.
+	 */
 	Population();
 
-	// construct
-	Population(int length, float mutationRate, int N_ind, int generation);
+	/**
+	 @brief Creates a Population with N_ind individuals with random genes.
+	 @param N_genes Number of genes of each individual.
+	 @param N_ind Number of individuals.
+	 @param mutationRate Probability of mutating a gene, between 0 and 1.
+	 @param generation Number of the generation.
+	 */
+	Population(int N_genes, int N_ind, float mutationRate, unsigned int generation);
 
-	DNA operator[](int i);
+	/**
+	 @brief Access the individual directly.
+	 @pre i must be between 0 and N_ind-1.
+	 @param i Position of the Individual.
+	 @return The individual at position i.
+	 */
+	DNA& operator[](int i);
 
-	// call fitness for every specimen
+	/**
+	 @brief Calculates the fitness of the population.
+	 @param scores Vector containing the scores of all of the individuals.
+	 */
 	void calculateFitness(vector<int> scores);
 
-	// reproduce
-	void naturalSelection();
-
-	// create new generation
-	Population generate(int length);
+	/**
+	 @brief Generates the next generation.
+	 @pre calculateFitness have already been executed.
+	 @pre Population has at least one individual.
+	 @return The next generation.
+	 */
+	Population generate();
 
-	// most fit
+	/**
+	 @brief Get position of the fittest individual. In case of having more than one, the first one is returned.
+	 @return The position of the fittest.
+	 */
 	int getBest();
 
-	// finished
-	bool isFinished();
-
+	/**
+	 @brief Get the number of the generation.
+	 @return The number of the generation.
+	 */
 	int getGenerations();
 
+	/**
+	 @brief Get the average fitness of the population.
+	 @return The average fitness of the population, between 0 and 1.
+	 */
 	float getAverage();
 
+	/**
+	 @brief Get all of the genes of the individuals.
+	 @return Vector of vector of genes. Each vector represents an individual. Each value represents a gene.
+	 */
 	vector< vector<float> > allValues();
+
+private:
+
+	/// @brief Probability of mutation between 0 and 1.
+	float mutationRate;
+
+	/// @brief Contains all of the individuals.
+	vector<DNA> population;
+
+	/// @brief Creates a temporary reproduction pool.
+	vector<DNA> pool;
+
+	/// @brief Number of the generation.
+	unsigned int generation;
+
+	/**
+	 @brief Fills the reproduction pool based on the fitness of every individual. The fittest have more probabilities of being selected out of the reproduction pool.
+	 */
+	void naturalSelection();
+
 };
 
 #endif /* Population_hpp */