public void WorstGenomesAreNeverWinners()
{
// Create some genomes.
int numberGenomes = 20;
var genomes = this.CreateGenomesAdheringToParameterTree(numberGenomes);
// Create a configuration using a certain winner percentage and mini tournament size.
double winnerPercentage = 0.1;
int miniTournamentSize = 10;
AlgorithmTunerConfiguration configuration = new AlgorithmTunerConfiguration.AlgorithmTunerConfigurationBuilder()
.SetTournamentWinnerPercentage(winnerPercentage)
.SetMaximumMiniTournamentSize(miniTournamentSize)
.Build(maximumNumberParallelEvaluations: 1);
// Create tournament selector using an evaluator which sorts by a certain parameter, highest first.
var tournamentSelectorProps = Props.Create(
() =>
new TournamentSelector <ExtractIntegerValue, TestInstance, IntegerResult>(
new ExtractIntegerValueCreator(),
new SortByValue(),
configuration,
this._resultStorageActorRef,
TournamentSelectorTest.CreateParameterTree()));
var tournamentSelector = this.Sys.ActorOf(tournamentSelectorProps, name: TournamentSelectorTest.SpecialTournamentSelectorName);
// Try selecting the best genomes via mini tournaments multiple times and make sure the worst genomes never
// get chosen:
int worstPossibleWinnerValue = miniTournamentSize - (int)(winnerPercentage * miniTournamentSize);
for (int i = 0; i < 15; i++)
{
// Send a select command.
tournamentSelector.Tell(new SelectCommand <TestInstance>(genomes, this._singleTestInstance, 0));
// Wait for results.
var results = this.ExpectMsg <SelectionResultMessage <IntegerResult> >();
// Make sure none belongs to the worst genomes.
foreach (var genome in results.CompetitiveParents)
{
int geneValue =
(int)genome.CreateMutableGenome().GetGeneValue(ExtractIntegerValue.ParameterName).GetValue();
Assert.True(
geneValue >= worstPossibleWinnerValue,
$"Found a winner with value {geneValue}, but expected at least {worstPossibleWinnerValue}.");
}
}
}
public void WinnersAreSortedCorrectly()
{
// Build configuration with a specific winner percentage and tournament size.
AlgorithmTunerConfiguration config = new AlgorithmTunerConfiguration.AlgorithmTunerConfigurationBuilder()
.SetTournamentWinnerPercentage(0.5)
.SetMaximumMiniTournamentSize(2)
.Build(maximumNumberParallelEvaluations: 1);
// Build tournament selector selecting winners by a specific parameter.
var tournamentSelector = this.Sys.ActorOf(
props: Props.Create(
() => new TournamentSelector <ExtractIntegerValue, TestInstance, IntegerResult>(
new ExtractIntegerValueCreator(),
new SortByValue(),
config,
this._resultStorageActorRef,
TournamentSelectorTest.CreateParameterTree())),
name: TournamentSelectorTest.SpecialTournamentSelectorName);
// Send selection command.
int numberGenomes = 4;
var genomes = this.CreateGenomesAdheringToParameterTree(numberGenomes);
tournamentSelector.Tell(new SelectCommand <TestInstance>(genomes, this._singleTestInstance, 0));
// Wait for results.
var results = this.ExpectMsg <SelectionResultMessage <IntegerResult> >();
// Check that they are sorted correctly.
var sortedResults = results.CompetitiveParents
.OrderByDescending(
genome =>
(int)genome.CreateMutableGenome().GetGeneValue(ExtractIntegerValue.ParameterName).GetValue());
Assert.True(
sortedResults.SequenceEqual(results.CompetitiveParents, new ImmutableGenome.GeneValueComparer()),
$"Expected winners sorted like {TestUtils.PrintList(sortedResults)}, but were {TestUtils.PrintList(results.CompetitiveParents)}.");
}
