/// <summary>
/// Tries to load a new genome out of the data
/// </summary>
/// <param name="data"></param>
public void LoadGenome(ref JsonWriterReader.GenomeData data)
{
if (data.weights.Count != 0)
{
Genome bestGenome = CreateGenomeWithoutWeights();
bestGenome.weights = data.weights;
if (_population.Count > 0)
{//if there are already memebers, find the worst one to replace
int worstGenome = 0;
float fitness = _population[0].fitness;
for (int i = 1; i < _population.Count; i++)
{
if (_population[i].fitness < fitness)
{
fitness = _population[i].fitness;
worstGenome = i;
}
}
_population[worstGenome].id = bestGenome.id;
_population[worstGenome].weights = bestGenome.weights;
}
else
{//otherwise just add it into the population
_population.Add(bestGenome);
}
}
}
/// <summary>
/// Loads the best genome into all of the agents.
/// </summary>
void LoadBestGenomes()
{
JsonWriterReader.GenomeData data = LoadBestGenome();
NeuralNetwork neuralNetwork = new NeuralNetwork();
if (data != null)
{//if the data isn't null
//create the best genome
Genome genome = _geneticAlgorithm.CreateGenomeFromData(LoadBestGenome());
//set up a neural network with that genome
neuralNetwork.SetupFromGenome(genome, _networkStructure);
for (int i = 0; i < _agents.Count; i++)
{//set each member with that network
_agents[i].InitializeNeuralNetwork(neuralNetwork);
}
}
else
{//otherwise create a new neural network for each memeber.
for (int i = 0; i < _agents.Count; i++)
{
neuralNetwork.Create(_networkStructure);
_agents[i].InitializeNeuralNetwork(neuralNetwork);
}
}
}
/// <summary>
/// Loads the best genome to add into the population.
/// </summary>
void LoadBestGenomeIntoPopulation()
{
JsonWriterReader.GenomeData data = LoadBestGenome();
if (data != null)
{//if not null, add it into the population
_geneticAlgorithm.LoadGenome(ref data);
}
}
/// <summary>
/// Saves currently the best genome
/// </summary>
void SaveBestGenome()
{
Genome bestGenome = _geneticAlgorithm.GetBestGenome();
JsonWriterReader.GenomeData data = new JsonWriterReader.GenomeData(bestGenome.weights);
string path = "BestGenomeWeights-" + data.weights.Count + "_Generation-" + _geneticAlgorithm.generation;
JsonWriterReader.WriteJson(path + ".json", ref data);
}
/// <summary>
/// Takes in the given data and if its not empty,
/// It generated a new genome with the data from the weights.
/// Otherwise it creates a new random genome
/// </summary>
/// <param name="data"></param>
/// <returns></returns>
public Genome CreateGenomeFromData(JsonWriterReader.GenomeData data)
{
if (data.weights.Count != 0)
{
Genome bestGenome = CreateGenomeWithoutWeights();
bestGenome.weights = data.weights;
return(bestGenome);
}
else
{
return(CreateNewGenome());
}
}
