public GeneticAlgorithm(int populationSize, int dnaSize, float mutationRate, BotVersion botVersion)
{
nextGame = 0;
scoreSum = 0;
generation = 1;
TBController.UpdateUIGeneration(generation);
this.mutationRate = mutationRate;
this.botVersion = botVersion;
population = new List <TetrisDNA>(); //A new random population is created
for (int i = 0; i < populationSize; i++)
{
TetrisDNA tetrisDNA = new TetrisDNA(dnaSize);
tetrisDNA.SetRandomWeights();
population.Add(tetrisDNA);
}
if (population.Count > 0)
{
best = population[0];
}
}
//When all the individuals have been tested, a new generation is created
public void NewGeneration()
{
if (population.Count <= 0)
{
return;
}
//The current generation data will be saved in a log file
SaveCurrentGeneration();
List <TetrisDNA> newPopulation = new List <TetrisDNA>();
for (int i = 0; i < population.Count; i++)
{
//Selection
TetrisDNA parent1 = ChooseParent();
TetrisDNA parent2 = ChooseParent();
//Crossover
TetrisDNA child = parent1.Crossover(parent2);
//Mutation
child.Mutate(mutationRate);
newPopulation.Add(child);
}
population = newPopulation;
generation++;
TBController.UpdateUIGeneration(generation);
nextGame = 0;
scoreSum = 0;
if (population.Count > 0)
{
best = population[0];
}
}
//When a game ends, the TetrisBoardController sends data about this game. The most important one, the score
public void SetDataFromLastGame(float score, int pieces, int lines, int level)
{
population[nextGame].SetScore(score);
population[nextGame].SetPieces(pieces);
population[nextGame].SetLines(lines);
population[nextGame].SetLevel(level);
scoreSum += score;
if (best.GetScore() < score)
{
best = population[nextGame];
}
nextGame++;
//If all the individuals have been tested, a new generation have to be created
if (nextGame >= population.Count)
{
NewGeneration();
}
}