/// <summary>
/// Invokes the mutation method on all agents in the population.
/// </summary>
/// <param name="mutator">The mutation method that defines how the population should be mutated.</param>
/// <param name="mutationProbability">The probability for an agent to be mutated.</param>
/// <param name="mutationProbilityGene">The probability for a gene to be mutated.</param>
/// <param name="random">The random generator that produces random numbers used in the method to determine
/// if an agent or a gene should be mutated.</param>
public void MakeMutations(IMutator mutator, double mutationProbability, double mutationProbilityGene, IRandomNumberGenerator random)
{
// Mutate all agents in population
for (int i = 0; i < Agents.Count; i++)
{
// Check if agent should be mutated
double randomDouble = random.GetDouble(0, 1);
if (randomDouble < mutationProbability)
{
Agents[i].Mutate(mutator, mutationProbilityGene, random);
}
}
}
/// <summary>
/// Goes through every gene and randomize the gene if probabilty hit.
/// </summary>
/// <param name="genes"></param>
/// <param name="mutationProbabilityGene"></param>
/// <param name="random"></param>
/// <returns></returns>
public Gene[] MakeMutation(Gene[] genes, double mutationProbabilityGene, IRandomNumberGenerator random)
{
for (int i = 0; i < genes.Length; i++)
{
// Check if this gene should be mutated
double randomDouble = random.GetDouble(0, 1);
if (randomDouble < mutationProbabilityGene)
{
// Overwrite with new random gene
genes[i] = new Gene(random);
}
}
return(genes);
}
/// <summary>
/// Returns selected agents based on the Roulette wheel selection method.
/// </summary>
/// <param name="agents"></param>
/// <param name="selectionSize"></param>
/// <param name="random"></param>
/// <returns></returns>
public List <Agent> MakeSelection(List <Agent> agents, int selectionSize, IRandomNumberGenerator random)
{
double totalFitness = 0;
List <double> agentProbabilities = new List <double>();
List <Agent> selectedAgents = new List <Agent>();
// Get total fitnes
for (int i = 0; i < agents.Count; i++)
{
// Sum fitness values
totalFitness += agents[i].Fitness;
}
// Make agent probabilities
for (int i = 0; i < agents.Count; i++)
{
agentProbabilities.Add(agents[i].Fitness / totalFitness);
}
double randomNumber = 0;
double total = 0;
int counter = 0;
bool agentFound = false;
for (int i = 0; i < selectionSize; i++)
{
// Get new random number
randomNumber = random.GetDouble(0, 1);
// Find angent match
for (int j = 0; j < agents.Count && !agentFound; j++)
{
total += agentProbabilities[j];
if (total >= randomNumber)
{
selectedAgents.Add(agents[j]);
agentFound = true;
}
}
Debug.WriteLine(++counter);
total = 0;
agentFound = false;
}
return(selectedAgents);
}
/// <summary>
/// Makes a random gene.
/// </summary>
/// <param name="random"></param>
public Gene(IRandomNumberGenerator random)
{
Value = random.GetDouble(-1, 1);
}
