public void CheckOnePointRecombinationFromBest()
{
using (var source = RandomSource.DrillIn())
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var best = new Genome(parameters, tracker, true);
var worst = new Genome(parameters, tracker, true);
// Act
source.GetParanoid();
source.PushLimitedNexts(1, 3); // crossover points
source.PushNextBools(true); // start from best
var result = best.Mate(worst, CrossoverType.OnePoint);
// Assert
Assert.Equal(result.NeatChromosome[0].Weight, best.NeatChromosome[0].Weight);
for (var i = 1; i < result.NeatChromosome.Count; i++)
{
Assert.Equal(result.NeatChromosome[i].Weight, worst.NeatChromosome[i].Weight);
}
}
}
public void SanityCheck()
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var genome = new Genome(parameters, tracker, false);
// Act
// Assert
Assert.Equal(0, genome.VacantConnectionCount);
// Act
genome.RemoveConnection(1);
// Assert
Assert.Equal(1, genome.VacantConnectionCount);
// Act
genome.AddConnection(0);
// Assert
Assert.Equal(0, genome.VacantConnectionCount);
}
/// <summary>
/// Creates a new innovation traker.
/// </summary>
/// <param name="name">The innovation tracker name.</param>
/// <param name="initialNodeCount">The initial node count.</param>
internal static void CreateInnovationTracker(string name, uint initialNodeCount)
{
if (!_innovationTrackers.ContainsKey(name))
{
_innovationTrackers[name] = new InnovationTracker(initialNodeCount);
}
}
public void CheckTwoPointRecombinationOfSingleGene()
{
// TODO fix crossover, make this one green
using (var source = RandomSource.DrillIn())
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var best = new Genome(parameters, tracker, true);
var worst = new Genome(parameters, tracker, true);
// Act
source.GetParanoid();
source.PushLimitedNexts(2, 2); // crossover points
source.PushNextBools(true); // start from best
var result = best.Mate(worst, CrossoverType.TwoPoints);
// Assert
Assert.Equal(result.NeatChromosome[2].Weight, worst.NeatChromosome[2].Weight);
for (var i = 0; i < result.NeatChromosome.Count; i++)
{
if (i == 2)
{
continue;
}
Assert.Equal(result.NeatChromosome[i].Weight, best.NeatChromosome[i].Weight);
}
}
}
public void CheckTrackerSanity()
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var first = new Genome(parameters, tracker, false);
var second = new Genome(parameters, tracker, false);
// Act
Assert.Equal(5, first.NeatChromosome.Count);
Assert.Equal(5, second.NeatChromosome.Count);
first.SplitConnection(1);
second.SplitConnection(1);
// Assert
Assert.Equal(6, first.NeatChromosome.Count);
Assert.Equal(6, second.NeatChromosome.Count);
for (var i = 0; i < first.NeatChromosome.Count; i++)
{
var firstGene = first.NeatChromosome[i];
var secondGene = second.NeatChromosome[i];
Assert.Equal(firstGene.Id, secondGene.Id);
Assert.Equal(firstGene.SourceId, secondGene.SourceId);
Assert.Equal(firstGene.TargetId, secondGene.TargetId);
}
}
public void CheckLinksAmbiguityHandling()
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var first = new Genome(parameters, tracker, false);
var second = new Genome(parameters, tracker, false);
// Act
Assert.True(first.NeatChromosome[1].SourceId == 1 && first.NeatChromosome[1].TargetId == 4);
Assert.True(second.NeatChromosome[1].SourceId == 1 && second.NeatChromosome[1].TargetId == 4);
first.SplitConnection(1);
second.SplitConnection(1);
while (second.VacantConnectionCount > 0) // make fully connected network to ensure our link is there
{
second.AddConnection(0);
}
// Assert
var linkGene = Assert.Single(second.NeatChromosome, gene => gene.SourceId == 1 && gene.TargetId == 4);
Assert.DoesNotContain(first.NeatChromosome, gene => gene.Id == linkGene.Id);
}
public void AddConnectionsOneByOneFeedforward()
{
// ReSharper disable once RedundantArgumentDefaultValue
var parameters = new NetworkParameters(3, 1, NetworkType.FeedForward)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var genome = new Genome(parameters, tracker, false);
var currentConnections = new List <string>
{
"0b->4e", "1s->4e", "2s->4e", "3s->4e"
};
AssertCurrentConnections(genome, currentConnections);
genome.SplitConnection(0); // 0 -> 4 into 0 -> 5 -> 4
currentConnections.ChangeCollection(new[] { "0b->4e" }, new[] { "0b->5h", "5h->4e" });
AssertCurrentConnections(genome, currentConnections);
genome.SplitConnection(4); // 0 -> 5 -> 4 into 0 -> 6 -> 5 -> 4
currentConnections.ChangeCollection(new[] { "0b->5h" }, new[] { "0b->6h", "6h->5h" });
AssertCurrentConnections(genome, currentConnections);
genome.SplitConnection(1); // 2 -> 4 into 2 -> 7 -> 4
currentConnections.ChangeCollection(new[] { "2s->4e" }, new[] { "2s->7h", "7h->4e" });
AssertCurrentConnections(genome, currentConnections);
var initialLayers = genome.NetworkTopology.LayerRanges.ToArray();
var initialLinksCount = genome.NetworkTopology.Links.Sum(l => l.Count);
genome.AddConnection(15); // 5h->7h
AssertNoChanges();
genome.AddConnection(6); // 7h->5h
AssertNoChanges();
genome.AddConnection(9); // 5h->6h
AssertNoChanges();
genome.AddConnection(9); // 7h->6h
AssertNoChanges();
genome.AddConnection(12); // 6h->7h
genome.NetworkTopology.Links.Sum(l => l.Count).Should().Be(initialLinksCount + 1, "added allowed connection");
genome.NetworkTopology.LayerRanges.Should().BeEquivalentTo(initialLayers, "expected no changes in layer structure");
void AssertNoChanges()
{
genome.NetworkTopology.Links.Sum(l => l.Count).Should().Be(initialLinksCount, "expected no changes after adding recurrent connections");
genome.NetworkTopology.LayerRanges.Should().BeEquivalentTo(initialLayers, "expected no changes after adding recurrent connections");
}
}
public void AddConnectionsOneByOneRecurrent()
{
(Genome genome, List <string> currentConnections, List <string> vacantConnections) CreateGenome()
{
// ReSharper disable once RedundantArgumentDefaultValue
var parameters = new NetworkParameters(3, 1, NetworkType.Recurrent)
{
InitialConnectionDensity = 1f
};
var tracker = new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var genome = new Genome(parameters, tracker, false);
var currentConnections = new List <string>
{
"0b->4e", "1s->4e", "2s->4e", "3s->4e", "4e->4e"
};
var vacantConnections = new List <string>();
AssertCurrentConnections(genome, currentConnections);
AssertVacantConnections(genome, vacantConnections);
// Act
genome.SplitConnection(0);
currentConnections.ChangeCollection(new[] { "0b->4e" }, new[] { "0b->5h", "5h->4h" });
vacantConnections.AddRange(new[] { "0b->4e", "1s->5h", "2s->5h", "3s->5h", "5h->5h", "4e->5h" });
AssertCurrentConnections(genome, currentConnections);
AssertVacantConnections(genome, vacantConnections);
genome.SplitConnection(5);
currentConnections.ChangeCollection(new[] { "0b->5h" }, new[] { "0b->6h", "6h->5h" });
vacantConnections.AddRange(new[] { "0b->5h", "1s->6h", "2s->6h", "3s->6h", "6h->6h", "5h->6h", "6h->4e", "4e->6h" });
AssertCurrentConnections(genome, currentConnections);
AssertVacantConnections(genome, vacantConnections);
genome.SplitConnection(1);
currentConnections.ChangeCollection(new[] { "2s->4e" }, new[] { "2s->7h", "7h->4e" });
vacantConnections.AddRange(new[] { "2s->4e", "0b->7h", "1s->7h", "3s->7h", "7h->7h", "5h->7h", "6h->7h", "7h->6h", "7h->5h", "4e->7h" });
AssertCurrentConnections(genome, currentConnections);
AssertVacantConnections(genome, vacantConnections);
vacantConnections.Should().HaveCount(24);
return(genome, currentConnections, vacantConnections);
}
var expectedAddStraightOrder = new[]
{
"0b->4e", "2s->4e", // outerConnections
"0b->5h", "1s->5h", "2s->5h", "3s->5h", "4e->5h", "5h->5h", "7h->5h", // to 5h
"1s->6h", "2s->6h", "3s->6h", "4e->6h", "5h->6h", "6h->6h", "7h->6h", // to 6h
"0b->7h", "1s->7h", "3s->7h", "4e->7h", "5h->7h", "6h->7h", "7h->7h", // to 7h
"6h->4e" // from hidden to effectors
};
TestAddConnections(CreateGenome, expectedAddStraightOrder);
}
public void SimpleNetworkCheck()
{
using (var source = RandomSource.DrillIn())
{
// Arrange
for (var i = 0; i < 10; i++)
{
source.PushNextFloats(0.6f); // identity weights and density chances
}
source.GetParanoid();
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var genome = new Genome(parameters, tracker, false);
var network = new RecurrentNetwork();
#region Network initialization
network.AddNeuron(0, 0);
network.AddNeuron(1, 0);
network.AddNeuron(2, 0);
network.AddNeuron(3, 0);
network.AddNeuron(4, 1);
network.AddConnection(0, 4, 1f);
network.AddConnection(1, 4, 1f);
network.AddConnection(2, 4, 1f);
network.AddConnection(3, 4, 1f);
network.AddConnection(4, 4, 1f);
#endregion
float[] result = null;
for (var i = 0; i < 5; i++)
{
for (var j = 0; j < 3; j++)
{
genome.Network.Sensors[j] = 0.5f;
}
genome.Network.Activate();
result = network.Activate(new[] { 1f, 0.5f, 0.5f, 0.5f });
}
Assert.Equal(result[0], genome.Network.Effectors[0]);
}
}
public void SplitConnectionTwoLayer()
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var genome = new Genome(parameters, tracker, false);
// Act
genome.SplitConnection(0); // 0 -> 4 into 0 -> 5 -> 4
genome.SplitConnection(5); // 0 -> 5 -> 4 into 0 -> 6 -> 5 -> 4
// Assert
Assert.Equal(14, genome.VacantConnectionCount);
}
public void CheckLinkResurrection()
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var genome = new Genome(parameters, tracker, false);
// Act
Assert.Equal(0, genome.VacantConnectionCount);
var oldId = genome.NeatChromosome[1].Id;
genome.RemoveConnection(1);
Assert.Equal(1, genome.VacantConnectionCount);
genome.AddConnection(0);
// Assert
Assert.Single(genome.NeatChromosome, gene => gene.Id == oldId);
}
public void CheckDisjointsAndEtcAreTakenFromBest()
{
// TODO fix crossover, make this one green
using (var source = RandomSource.DrillIn())
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var best = new Genome(parameters, tracker, true);
var worst = new Genome(parameters, tracker, true);
best.SplitConnection(1);
// Act
source.GetParanoid();
source.PushLimitedNexts(0, 2); // crossover points - all from worst
source.PushNextBools(true); // start from best
var result = best.Mate(worst, CrossoverType.OnePoint);
// Assert
Assert.Equal(best.NeatChromosome.Count, result.NeatChromosome.Count);
for (var i = 0; i < result.NeatChromosome.Count - 2; i++)
{
var parentGene = Assert.Single(worst.NeatChromosome, g => g.Id == result.NeatChromosome[i].Id);
Assert.Equal(result.NeatChromosome[i].Weight, parentGene.Weight);
}
for (var i = result.NeatChromosome.Count - 2; i < result.NeatChromosome.Count; i++)
{
Assert.Equal(result.NeatChromosome[i].Id, best.NeatChromosome[i].Id);
Assert.Equal(result.NeatChromosome[i].Weight, best.NeatChromosome[i].Weight);
}
}
}
public void LayeredNetworkCheck()
{
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var genome = new Genome(parameters, tracker, false);
genome.SplitConnection(0);
genome.SplitConnection(2);
genome.SplitConnection(genome.NeatChromosome.Single(g => g.SourceId == 5).Id);
while (genome.VacantConnectionCount > 0)
{
genome.AddConnection(Neat.Utils.RandomSource.Next(genome.VacantConnectionCount));
}
var network = new RecurrentNetwork();
void AddConnectionAndCopyWeight(int sourceId, int targetId)
{
var weight = genome.NeatChromosome.Single(g => g.SourceId == sourceId && g.TargetId == targetId).Weight;
network.AddConnection(sourceId, targetId, weight);
}
#region Network initialization
network.AddNeuron(0, 0);
network.AddNeuron(1, 0);
network.AddNeuron(2, 0);
network.AddNeuron(3, 0);
network.AddNeuron(5, 1);
network.AddNeuron(6, 1);
network.AddNeuron(7, 2);
network.AddNeuron(4, 3);
for (var i = 0; i < 4; i++)
{
for (var j = 4; j < 8; j++)
{
AddConnectionAndCopyWeight(i, j);
}
}
for (var i = 4; i < 8; i++)
{
for (var j = 4; j < 8; j++)
{
AddConnectionAndCopyWeight(i, j);
}
}
Assert.Equal(network.ConnectionsCount, genome.NeatChromosome.Count);
#endregion
float[] result = null;
for (var i = 0; i < 5; i++)
{
var values = new[]
{
1f,
Neat.Utils.RandomSource.Next(),
Neat.Utils.RandomSource.Next(),
Neat.Utils.RandomSource.Next()
};
for (var j = 0; j < 3; j++)
{
genome.Network.Sensors[j] = values[j + 1];
}
genome.Network.Activate();
result = network.Activate(values);
}
Assert.Equal(result[0], genome.Network.Effectors[0]);
}
