/// <summary>
/// Perform one operation.
/// </summary>
public void PerformTask()
{
bool success = false;
int tries = _train.MaxOperationErrors;
do
{
try
{
// choose an evolutionary operation (i.e. crossover or a type of
// mutation) to use
IEvolutionaryOperator opp = _train.Operators
.PickMaxParents(_rnd,
_species.Members.Count);
_children[0] = null;
// prepare for either sexual or asexual reproduction either way,
// we need at least one parent, which is the first parent.
//
// Chose the first parent, there must be at least one genome in
// this species
_parents[0] = ChooseParent();
// if the number of individuals in this species is only
// one then we can only clone and perhaps mutate, otherwise use
// the crossover probability to determine if we are to use
// sexual reproduction.
if (opp.ParentsNeeded > 1)
{
int numAttempts = 5;
_parents[1] = ChooseParent();
while (_parents[0] == _parents[1] &&
numAttempts-- > 0)
{
_parents[1] = ChooseParent();
}
// success, perform crossover
if (_parents[0] != _parents[1])
{
opp.PerformOperation(_rnd, _parents, 0,
_children, 0);
}
}
else
{
// clone a child (asexual reproduction)
opp.PerformOperation(_rnd, _parents, 0,
_children, 0);
_children[0].Population = _parents[0].Population;
}
// process the new child
foreach (IGenome child in _children)
{
if (child != null)
{
child.Population = _parents[0].Population;
child.BirthGeneration = _train.IterationNumber;
_train.CalculateScore(child);
if (!_train.AddChild(child))
{
return;
}
success = true;
}
}
}
catch (AIFHError)
{
tries--;
if (tries < 0)
{
throw new AIFHError(
"Could not perform a successful genetic operaton after "
+ _train.MaxOperationErrors
+ " tries.");
}
}
catch (Exception t)
{
if (!_train.IgnoreExceptions)
{
throw;
}
}
} while (!success);
}
