/// <summary>
/// Constructs and initializes the maze navigator initialization algorithm (fitness using generational selection). In
/// particular, this sets additional novelty search configuration parameters.
/// </summary>
/// <param name="xmlConfig">The XML configuration for the initialization algorithm.</param>
/// <param name="isAcyclic">Flag indicating whether the network is acyclic (i.e. does not have recurrent connections).</param>
/// <param name="numSuccessfulAgents">The minimum number of successful maze navigators that must be produced.</param>
/// <param name="numUnsuccessfulAgents">The minimum number of unsuccessful maze navigators that must be produced.</param>
/// <returns>The constructed initialization algorithm.</returns>
public override void SetAlgorithmParameters(XmlElement xmlConfig, bool isAcyclic, int numSuccessfulAgents,
int numUnsuccessfulAgents)
{
// Set the boiler plate MCC parameters and minimal criterions
base.SetAlgorithmParameters(xmlConfig, isAcyclic, numSuccessfulAgents, numUnsuccessfulAgents);
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(xmlConfig,
"InitBehaviorConfig");
// Read in the novelty archive parameters
ExperimentUtils.ReadNoveltyParameters(xmlConfig, out _archiveAdditionThreshold,
out _archiveThresholdDecreaseMultiplier, out _archiveThresholdIncreaseMultiplier,
out _maxGenerationArchiveAddition, out _maxGenerationsWithoutArchiveAddition);
// Read in nearest neighbors for behavior distance calculations
_nearestNeighbors = XmlUtils.GetValueAsInt(xmlConfig, "NearestNeighbors");
// Read in steady-state specific parameters
_batchSize = XmlUtils.GetValueAsInt(xmlConfig, "OffspringBatchSize");
_populationEvaluationFrequency = XmlUtils.GetValueAsInt(xmlConfig, "PopulationEvaluationFrequency");
}
/// <inheritdoc />
/// <summary>
/// Initializes the MCC maze navigation experiment by reading in all of the configuration parameters and
/// setting up the bootstrapping/initialization algorithm.
/// </summary>
/// <param name="name">The name of the experiment.</param>
/// <param name="xmlConfig">The reference to the XML configuration file.</param>
/// <param name="population1EvolutionLogger">The navigator evolution data logger.</param>
/// <param name="population1PopulationLogger">The navigator population logger.</param>
/// <param name="population1GenomeLogger">The navigator genome logger.</param>
/// <param name="population2EvolutionLogger">The maze evolution data logger.</param>
/// <param name="population2PopulationLogger">The maze population logger.</param>
/// <param name="population2GenomeLogger">The maze genome logger.</param>
public virtual void Initialize(string name, XmlElement xmlConfig,
IDataLogger population1EvolutionLogger = null, IDataLogger population1PopulationLogger = null,
IDataLogger population1GenomeLogger = null, IDataLogger population2EvolutionLogger = null,
IDataLogger population2PopulationLogger = null, IDataLogger population2GenomeLogger = null)
{
// Set boiler plate properties
Name = name;
Description = XmlUtils.GetValueAsString(xmlConfig, "Description");
ActivationScheme = ExperimentUtils.CreateActivationScheme(xmlConfig, "Activation");
ParallelOptions = ExperimentUtils.ReadParallelOptions(xmlConfig);
// Set the genome parameters
NeatGenomeParameters = ExperimentUtils.ReadNeatGenomeParameters(xmlConfig);
NeatGenomeParameters.FeedforwardOnly = ActivationScheme.AcyclicNetwork;
MazeGenomeParameters = ExperimentUtils.ReadMazeGenomeParameters(xmlConfig);
// Configure evolutionary algorithm parameters
AgentDefaultPopulationSize = XmlUtils.GetValueAsInt(xmlConfig, "AgentPopulationSize");
MazeDefaultPopulationSize = XmlUtils.GetValueAsInt(xmlConfig, "MazePopulationSize");
AgentSeedGenomeCount = XmlUtils.GetValueAsInt(xmlConfig, "AgentSeedGenomeCount");
MazeSeedGenomeCount = XmlUtils.GetValueAsInt(xmlConfig, "MazeSeedGenomeCount");
AgentNumSpecies = XmlUtils.GetValueAsInt(xmlConfig, "AgentNumSpecies");
MazeNumSpecies = XmlUtils.GetValueAsInt(xmlConfig, "MazeNumSpecies");
BehaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(xmlConfig,
"BehaviorConfig");
NavigatorBatchSize = XmlUtils.GetValueAsInt(xmlConfig, "NavigatorOffspringBatchSize");
MazeBatchSize = XmlUtils.GetValueAsInt(xmlConfig, "MazeOffspringBatchSize");
// Set run-time bounding parameters
MaxGenerations = XmlUtils.TryGetValueAsInt(xmlConfig, "MaxGenerations");
MaxEvaluations = XmlUtils.TryGetValueAsULong(xmlConfig, "MaxEvaluations");
// Set experiment-specific parameters
MinSuccessDistance = XmlUtils.GetValueAsInt(xmlConfig, "MinSuccessDistance");
MazeHeight = XmlUtils.GetValueAsInt(xmlConfig, "MazeHeight");
MazeWidth = XmlUtils.GetValueAsInt(xmlConfig, "MazeWidth");
MazeQuadrantHeight = XmlUtils.GetValueAsInt(xmlConfig, "MazeQuadrantHeight");
MazeQuadrantWidth = XmlUtils.GetValueAsInt(xmlConfig, "MazeQuadrantWidth");
MazeScaleMultiplier = XmlUtils.GetValueAsInt(xmlConfig, "MazeScaleMultiplier");
// Get success/failure criteria constraints
NumMazeSuccessCriteria = XmlUtils.GetValueAsInt(xmlConfig, "NumMazesSolvedCriteria");
NumAgentSuccessCriteria = XmlUtils.GetValueAsInt(xmlConfig, "NumAgentsSolvedCriteria");
NumAgentFailedCriteria = XmlUtils.GetValueAsInt(xmlConfig, "NumAgentsFailedCriteria");
// Read in the maximum number of initialization evaluations
_maxInitializationEvaluations = XmlUtils.GetValueAsUInt(xmlConfig, "MaxInitializationEvaluations");
// Initialize the initialization algorithm
_mazeNavigationInitializer =
ExperimentUtils.DetermineMCCInitializer(
xmlConfig.GetElementsByTagName("InitializationAlgorithmConfig", "")[0] as XmlElement);
// Setup initialization algorithm
_mazeNavigationInitializer.SetAlgorithmParameters(
xmlConfig.GetElementsByTagName("InitializationAlgorithmConfig", "")[0] as XmlElement,
ActivationScheme.AcyclicNetwork, NumAgentSuccessCriteria, 0);
// Pass in maze experiment specific parameters
// (note that a new maze structure is created here for the sole purpose of extracting the maze dimensions and calculating max distance to target)
_mazeNavigationInitializer.SetEnvironmentParameters(MinSuccessDistance,
new MazeDecoder(MazeScaleMultiplier).Decode(
new MazeGenomeFactory(MazeGenomeParameters, MazeHeight, MazeWidth, MazeQuadrantHeight,
MazeQuadrantWidth).CreateGenome(0)));
// The size of the randomly generated agent genome pool from which to evolve agent bootstraps
AgentInitializationGenomeCount = _mazeNavigationInitializer.PopulationSize;
}