Implementing Genetic Algorithm

.gitignore

@@ -2,6 +2,7 @@
 AdversarialSearch/Minimax/Main
 AdversarialSearch/Minimax/Main.dSYM/
 cmake-build-debug
+cmake-build-release
 build
 *.asta
 *.asta.lock

CMakeLists.txt

@@ -3,6 +3,7 @@ project(AIEngine)
 set(CMAKE_CXX_STANDARD 14)
 set(EXECUTABLE_OUTPUT_PATH ${PROJECT_BINARY_DIR}/build)
 add_subdirectory(AdversarialSearch/Minimax)
-add_subdirectory(NeuralNetwork/Common)
+add_subdirectory(Common)
 add_subdirectory(NeuralNetwork/Perceptron)
 add_subdirectory(NeuralNetwork/MLP)
+add_subdirectory("Search Heuristic/Genetic Algorithm")

Common/Random.cpp

@@ -0,0 +1,15 @@
+#include <cstdlib>
+#include <ctime>
+
+#include "Random.h"
+
+unsigned int RandomUtils::GetTime()
+{
+    const auto currentTime = static_cast<unsigned int>(time(nullptr));
+    return currentTime;
+}
+
+void RandomUtils::InitSeed(const unsigned int seed)
+{
+    srand(seed);
+}

Common/Random.h

@@ -0,0 +1,20 @@
+#pragma once
+
+#include <cstdlib>
+#include <type_traits>
+
+namespace RandomUtils
+{
+    unsigned int GetTime();
+
+    void InitSeed(unsigned int seed);
+
+    template <typename TArithmeticType,
+    typename = typename std::enable_if<std::is_arithmetic<TArithmeticType>::value, TArithmeticType>::type>
+    TArithmeticType range(const TArithmeticType minValue, const TArithmeticType maxValue)
+    {
+        const float randomValue = (std::rand() / (float) RAND_MAX);
+        const TArithmeticType result = minValue + randomValue * (maxValue - minValue);
+        return result;
+    }
+}

NeuralNetwork/MLP/CMakeLists.txt

@@ -1,7 +1,7 @@
 set(FILES
         ../Common/ActivationFunctions.cpp
-        ../Common/Random.cpp
-        ../Common/Matrix.cpp
+        ../../Common/Random.cpp
+        ../../Common/Matrix.cpp
         ../Perceptron/Neuron.cpp
         ../Perceptron/Perceptron.cpp
         Layer.cpp

NeuralNetwork/MLP/Main.cpp

@@ -1,6 +1,6 @@
 #include <iostream>
 #include <fstream>
-#include "../Common/Random.h"
+#include "../../Common/Random.h"
 #include "MLP.h"
 
 int propagate(MultiLayerPerceptron& mlp, std::vector<float> inputs, bool printResult)
@@ -37,7 +37,7 @@ void loadWeightsFromFile(const char* filePath, MultiLayerPerceptron& mlp)
 void trainXor2LayersMLP(const char* filePath)
 {
     std::cout << "XOR - 2 Layers (2, 1)" << std::endl;
-    random::initRandomSeed();
+    RandomUtils::InitSeed(RandomUtils::GetTime());
     std::vector<int> neuronsByLayerArr = std::vector<int> {2,1};
     bool isNetworkTrained = false;
     unsigned long iterations = 0;
@@ -65,7 +65,7 @@ void trainXor2LayersMLP(const char* filePath)
 void trainXor3LayersMLP(const char* filePath)
 {
     std::cout << "XOR - 3 Layers (2, 2, 1)" << std::endl;
-    random::initRandomSeed();
+    RandomUtils::InitSeed(RandomUtils::GetTime());
     std::vector<int> neuronsByLayerArr = std::vector<int> {2,2,1};
     bool isNetworkTrained = false;
     unsigned long iterations = 0;

NeuralNetwork/Perceptron/CMakeLists.txt

@@ -1,7 +1,7 @@
 set(FILES
         ../Common/ActivationFunctions.cpp
-        ../Common/Random.cpp
-        ../Common/Matrix.cpp
+        ../../Common/Random.cpp
+        ../../Common/Matrix.cpp
         Neuron.cpp
         Perceptron.cpp
         PerceptronTests.cpp

NeuralNetwork/Perceptron/Neuron.h

@@ -1,7 +1,7 @@
 #ifndef NEURALNETWORK_NEURON_H
 #define NEURALNETWORK_NEURON_H
 
-#include "../Common/Matrix.h"
+#include "../../Common/Matrix.h"
 
 class Neuron
 {

NeuralNetwork/Perceptron/Perceptron.cpp

@@ -1,17 +1,17 @@
 #include "Perceptron.h"
-#include "../Common/Random.h"
+#include "../../Common/Random.h"
 
 Perceptron::Perceptron(int weightsLength)
 {
     _neuron = std::make_unique<Neuron>();
     auto weights = std::make_unique<Matrix>(1, weightsLength);
     for (int c = 0; c < weights->getColumns(); ++c)
     {
-        float randomValue = random::range(-1.0f, 1.0f);
+        float randomValue = RandomUtils::range(-1.0f, 1.0f);
         weights->set(0,c,randomValue);
     }
     _neuron->setWeights(*weights);
-    float randomBias = random::range(-0.1f,0.1f);
+    float randomBias = RandomUtils::range(-0.1f, 0.1f);
     _neuron->setBias(randomBias);
     _activationFunction = noActivation;
 }

NeuralNetwork/Perceptron/PerceptronTests.cpp

@@ -1,5 +1,5 @@
 #include "Perceptron.h"
-#include "../Common/Random.h"
+#include "../../Common/Random.h"
 
 ///returns the expected output from given inputs
 float toExpectedOutput(Matrix& inputs)
@@ -11,19 +11,19 @@ float toExpectedOutput(Matrix& inputs)
     return 1.0f;
 }
 
-///Populate 'matrix' with random inputs in range -500.0/500.0
+///Populate 'matrix' with RandomUtils inputs in range -500.0/500.0
 void populateRandomInput(Matrix& matrix)
 {
     for (int r = 0; r < matrix.getRows(); ++r)
     {
-        float value = random::range(-500.0f, 500.0f);
+        float value = RandomUtils::range(-500.0f, 500.0f);
         matrix.set(r,0,value);
     }
 }
 
 int main(int argc, char* argv[])
 {
-    random::initRandomSeed();
+    RandomUtils::InitSeed(RandomUtils::GetTime());
     auto perceptron = std::make_unique<Perceptron>(2);
     perceptron->setActivationFunction(sign);
     int correctGuesses = 0;

Search Heuristic/Genetic Algorithm/CMakeLists.txt

@@ -0,0 +1,3 @@
+set(FILES Main.cpp
+        ../../Common/Random.cpp GeneticAlgorithm.cpp GeneticAlgorithm.h)
+add_executable(GeneticAlgorithm ${FILES})

Search Heuristic/Genetic Algorithm/GeneticAlgorithm.cpp

@@ -0,0 +1,5 @@
+//
+// Created by andrei.schuch on 1/30/2022.
+//
+
+#include "GeneticAlgorithm.h"

Search Heuristic/Genetic Algorithm/GeneticAlgorithm.h

@@ -0,0 +1,39 @@
+#pragma once
+
+#include "../../Common/Random.h"
+
+class GeneticAlgorithm
+{
+public:
+    void Crossover(int& lhs, int& rhs, const int index)
+    {
+        const int leftMask = 0xffffffff >> index;
+        const int rightMask = ~leftMask;
+
+        const int newLhs = (lhs & leftMask) | (rhs & rightMask);
+        const int newRhs = (rhs & leftMask) | (lhs & rightMask);
+
+        lhs = newLhs;
+        rhs = newRhs;
+    }
+
+    void Mutate(int& chromossome)
+    {
+        for (int i = 0; i < 32; i++)
+        {
+            if (RandomUtils::range(0.0, 1.0) > 0.001) continue;
+            const int geneMask = 1 << i;
+
+            //TODO
+        }
+    }
+
+    //void generateInitialPopulation(std::vector<int>& population);
+    //int getFitnessScore(int& chromosome);
+    //Order list elements based on fitness score (first == best, last == worst)
+    //void orderByFitnessScore(std::vector<int>& population);
+    //void selection(std::vector<int>& population);
+    //void farrow(std::vector<int>& population);
+    //void crossover(std::vector<int>& population);
+    //void mutation(std::vector<int>& population);
+};

Search Heuristic/Genetic Algorithm/Main.cpp

@@ -0,0 +1,39 @@
+#include <iostream>
+#include <stdlib.h>
+#include <algorithm>
+#include <vector>
+#include <ctime>
+
+#include "../../Common/Random.h"
+#include "bitset"
+#include "GeneticAlgorithm.h"
+
+// Population { [010], [1100], [1010] }
+// -> Chromosome [0001]
+//   -> Gene [0]
+
+int main()
+{
+    RandomUtils::InitSeed(RandomUtils::GetTime());
+    /*
+     * 1. Initial population
+     * 2. Fitness function
+     * 3. Selection
+     * 4. Crossover
+     * 5. Mutation
+     */
+
+    GeneticAlgorithm genericAlgorithm;
+    int lhs = 0xffff;
+    int rhs = 0xffff << 16;
+
+    std::cout << std::bitset<32>(lhs) << std::endl;
+    std::cout << std::bitset<32>(rhs) << std::endl << std::endl;
+
+    genericAlgorithm.Crossover(lhs, rhs, 1);
+
+    std::cout << std::bitset<32>(lhs) << std::endl;
+    std::cout << std::bitset<32>(rhs) << std::endl;
+
+    return 0;
+}