/// <summary>
/// Construct a neat trainer with a new population. The new population is
/// created from the specified parameters.
/// </summary>
/// <param name="calculateScore">The score calculation object.</param>
/// <param name="inputCount">The input neuron count.</param>
/// <param name="outputCount">The output neuron count.</param>
/// <param name="populationSize">The population size.</param>
public NEATTraining(ICalculateScore calculateScore,
int inputCount, int outputCount,
int populationSize)
{
this.inputCount = inputCount;
this.outputCount = outputCount;
CalculateScore = new GeneticScoreAdapter(calculateScore);
Comparator = new GenomeComparator(CalculateScore);
Population = new NEATPopulation(inputCount, outputCount,
populationSize);
Init();
}
/// <summary>
/// Construct neat training with an existing population.
/// </summary>
/// <param name="calculateScore">The score object to use.</param>
/// <param name="population">The population to use.</param>
public NEATTraining(ICalculateScore calculateScore,
IPopulation population)
{
if (population.Size() < 1)
{
throw new TrainingError("Population can not be empty.");
}
var genome = (NEATGenome)population.Genomes[0];
CalculateScore = new GeneticScoreAdapter(calculateScore);
Comparator = new GenomeComparator(CalculateScore);
Population = (population);
inputCount = genome.InputCount;
outputCount = genome.OutputCount;
Init();
}
/// <summary>
/// Construct a neat trainer with a new population.
/// </summary>
/// <param name="calculateScore">The score calculation object.</param>
/// <param name="inputCount">The input neuron count.</param>
/// <param name="outputCount">The output neuron count.</param>
/// <param name="populationSize">The population size.</param>
public NEATTraining(ICalculateScore calculateScore,
int inputCount, int outputCount,
int populationSize)
{
this.inputCount = inputCount;
this.outputCount = outputCount;
CalculateScore = new GeneticScoreAdapter(calculateScore);
Comparator = new GenomeComparator(CalculateScore);
Population = new BasicPopulation(populationSize);
// create the initial population
for (int i = 0; i < populationSize; i++)
{
Population.Add(
new NEATGenome(this, Population.AssignGenomeID(),
inputCount, outputCount));
}
Init();
}
/// <summary>
/// Construct neat training with an existing population.
/// </summary>
/// <param name="calculateScore">The score object to use.</param>
/// <param name="population">The population to use.</param>
public NEATTraining(ICalculateScore calculateScore,
IPopulation population)
{
if (population.Size() < 1)
{
throw new TrainingError("Population can not be empty.");
}
var genome = (NEATGenome) population.Genomes[0];
CalculateScore = new GeneticScoreAdapter(calculateScore);
Comparator = new GenomeComparator(CalculateScore);
Population = (population);
inputCount = genome.InputCount;
outputCount = genome.OutputCount;
Init();
}
/// <summary>
/// Construct a neat trainer with a new population. The new population is
/// created from the specified parameters.
/// </summary>
/// <param name="calculateScore">The score calculation object.</param>
/// <param name="inputCount">The input neuron count.</param>
/// <param name="outputCount">The output neuron count.</param>
/// <param name="populationSize">The population size.</param>
public NEATTraining(ICalculateScore calculateScore,
int inputCount, int outputCount,
int populationSize)
{
this.inputCount = inputCount;
this.outputCount = outputCount;
CalculateScore = new GeneticScoreAdapter(calculateScore);
Comparator = new GenomeComparator(CalculateScore);
Population = new NEATPopulation(inputCount, outputCount,
populationSize);
Init();
}
/// <summary>
/// Construct a neat trainer with a new population.
/// </summary>
/// <param name="calculateScore">The score calculation object.</param>
/// <param name="inputCount">The input neuron count.</param>
/// <param name="outputCount">The output neuron count.</param>
/// <param name="populationSize">The population size.</param>
public NEATTraining(ICalculateScore calculateScore,
int inputCount, int outputCount,
int populationSize)
{
this.inputCount = inputCount;
this.outputCount = outputCount;
CalculateScore = new GeneticScoreAdapter(calculateScore);
Comparator = new GenomeComparator(CalculateScore);
Population = new BasicPopulation(populationSize);
// create the initial population
for (int i = 0; i < populationSize; i++)
{
Population.Add(
new NEATGenome(this, Population.AssignGenomeID(),
inputCount, outputCount));
}
Init();
}
