/// <summary>
/// Maze Navigator MCS evaluator constructor.
/// </summary>
/// <param name="minSuccessDistance">The minimum distance from the target to be considered a successful run.</param>
/// <param name="behaviorCharacterizationFactory">The initialized behavior characterization factory.</param>
/// <param name="agentNumSuccessesCriteria">
/// The number of mazes that must be solved successfully in order to satisfy the
/// minimal criterion.
/// </param>
public MazeNavigatorMCCEvaluator(int minSuccessDistance,
IBehaviorCharacterizationFactory behaviorCharacterizationFactory, int agentNumSuccessesCriteria)
{
_behaviorCharacterizationFactory = behaviorCharacterizationFactory;
_agentNumSuccessesCriteria = agentNumSuccessesCriteria;
EvaluationCount = 0;
// Create factory for generating multiple mazes
_multiMazeWorldFactory = new MultiMazeNavigationWorldFactory <BehaviorInfo>(minSuccessDistance);
}
/// <summary>
/// Maze Environment MCS evaluator constructor.
/// </summary>
/// <param name="minSuccessDistance">The minimum distance from the target to be considered a successful run.</param>
/// <param name="behaviorCharacterizationFactory">The initialized behavior characterization factory.</param>
/// <param name="numAgentsSolvedCriteria">
/// The number of successful attempts at maze navigation in order to satisfy the
/// minimal criterion.
/// </param>
/// <param name="numAgentsFailedCriteria">
/// The number of failed attempts at maze navigation in order to satisfy the minimal
/// criterion.
/// </param>
public MazeEnvironmentMCCEvaluator(int minSuccessDistance,
IBehaviorCharacterizationFactory behaviorCharacterizationFactory, int numAgentsSolvedCriteria,
int numAgentsFailedCriteria)
{
_behaviorCharacterizationFactory = behaviorCharacterizationFactory;
_numAgentsSolvedCriteria = numAgentsSolvedCriteria;
_numAgentsFailedCriteria = numAgentsFailedCriteria;
// Create factory for maze world generation
_multiMazeWorldFactory = new MultiMazeNavigationWorldFactory <BehaviorInfo>(minSuccessDistance);
}
/// <summary>
/// Maze Navigator fitness initialization evaluator constructor.
/// </summary>
/// <param name="minSuccessDistance">The minimum distance from the target to be considered a successful run.</param>
/// <param name="maxDistanceToTarget">The maximum distance from the target possible.</param>
/// <param name="behaviorCharacterizationFactory">The initialized behavior characterization factory.</param>
/// <param name="startingEvaluations">The number of evaluations from which the evaluator is starting (defaults to 0).</param>
public MazeNavigatorNoveltySearchInitializationEvaluator(int minSuccessDistance,
int maxDistanceToTarget, IBehaviorCharacterizationFactory behaviorCharacterizationFactory,
ulong startingEvaluations = 0)
{
EvaluationCount = startingEvaluations;
_behaviorCharacterizationFactory = behaviorCharacterizationFactory;
// Create factory for generating mazes
_multiMazeWorldFactory = new MultiMazeNavigationWorldFactory <BehaviorInfo>(minSuccessDistance,
maxDistanceToTarget);
}
/// <inheritdoc />
/// <summary>
/// Maze Navigator fitness initialization evaluator constructor.
/// </summary>
/// <param name="minSuccessDistance">The minimum distance from the target to be considered a successful run.</param>
/// <param name="maxDistanceToTarget">The maximum distance from the target possible.</param>
/// <param name="initialMazeStructure">
/// The maze structure with which to seed the list of maze structures in the maze
/// factory.
/// </param>
/// <param name="behaviorCharacterizationFactory">The initialized behavior characterization factory.</param>
/// <param name="startingEvaluations">The number of evaluations from which the evaluator is starting (defaults to 0).</param>
public MazeNavigatorNoveltySearchInitializationEvaluator(int minSuccessDistance,
int maxDistanceToTarget, MazeStructure initialMazeStructure,
IBehaviorCharacterizationFactory behaviorCharacterizationFactory, ulong startingEvaluations = 0)
: this(
minSuccessDistance, maxDistanceToTarget, behaviorCharacterizationFactory, startingEvaluations)
{
// Add initial maze structure
_multiMazeWorldFactory.SetMazeConfigurations(new List <MazeStructure>(1)
{
initialMazeStructure
});
}
/// <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");
}
public override void Initialize(string name, XmlElement xmlConfig, IDataLogger evolutionDataLogger,
IDataLogger evaluationDataLogger)
{
base.Initialize(name, xmlConfig, evolutionDataLogger, evaluationDataLogger);
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(xmlConfig,
"BehaviorConfig");
// Read in number of offspring to produce in a single batch
_batchSize = XmlUtils.GetValueAsInt(xmlConfig, "OffspringBatchSize");
// Read in the minimal criteria update interval
_minimalCriteriaUpdateInterval = XmlUtils.GetValueAsInt(xmlConfig, "MinimalCriteriaUpdateInterval");
// Read in the bridging magnitude and number of applications
_bridgingMagnitude = XmlUtils.TryGetValueAsInt(xmlConfig, "BridgingMagnitude") ?? default(int);
_bridgingApplications = XmlUtils.TryGetValueAsInt(xmlConfig, "BridgingApplications") ?? default(int);
// Read in the number of seed genomes to generate to bootstrap the primary algorithm
SeedGenomeCount = XmlUtils.GetValueAsInt(xmlConfig, "SeedGenomeCount");
// Read in log file path/name
_evolutionDataLogger = evolutionDataLogger ??
ExperimentUtils.ReadDataLogger(xmlConfig, LoggingType.Evolution);
_evaluationDataLogger = evaluationDataLogger ??
ExperimentUtils.ReadDataLogger(xmlConfig, LoggingType.Evaluation);
// Setup the specific logging options based on parameters that are enabled/disabled
_experimentLogFieldEnableMap = new Dictionary<FieldElement, bool>();
// Enable or disable genome XML logging
if (SerializeGenomeToXml)
{
_experimentLogFieldEnableMap.Add(EvolutionFieldElements.ChampGenomeXml, true);
}
// Enable or disable primary fitness logging (causing utilization of auxiliary fitness)
if (_bridgingMagnitude > 0)
{
_experimentLogFieldEnableMap.Add(EvolutionFieldElements.ChampGenomeFitness, false);
}
// Log the MC threshold and location since it is dynamic
_experimentLogFieldEnableMap.Add(EvolutionFieldElements.MinimalCriteriaThreshold, true);
_experimentLogFieldEnableMap.Add(EvolutionFieldElements.MinimalCriteriaPointX, true);
_experimentLogFieldEnableMap.Add(EvolutionFieldElements.MinimalCriteriaPointY, true);
}
public override void Initialize(ExperimentDictionary experimentDictionary)
{
base.Initialize(experimentDictionary);
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(
experimentDictionary, true);
// Read in number of offspring to produce in a single batch
_batchSize = experimentDictionary.Primary_OffspringBatchSize ?? default(int);
// Read in log file path/name
_evolutionDataLogger = new McsExperimentEvaluationEntityDataLogger(experimentDictionary.ExperimentName);
_evaluationDataLogger =
new McsExperimentOrganismStateEntityDataLogger(experimentDictionary.ExperimentName);
}
public override void Initialize(string name, XmlElement xmlConfig, IDataLogger evolutionDataLogger,
IDataLogger evaluationDataLogger)
{
base.Initialize(name, xmlConfig, evolutionDataLogger, evaluationDataLogger);
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(xmlConfig,
"BehaviorConfig");
// Read in steady-state specific parameters
_batchSize = XmlUtils.GetValueAsInt(xmlConfig, "OffspringBatchSize");
_populationEvaluationFrequency = XmlUtils.GetValueAsInt(xmlConfig, "PopulationEvaluationFrequency");
// Read in MCS selection method
_mcsSelectionMethod = XmlUtils.TryGetValueAsString(xmlConfig, "McsSelectionMethod");
// Read in log file path/name
_evolutionDataLogger = evolutionDataLogger ??
ExperimentUtils.ReadDataLogger(xmlConfig, LoggingType.Evolution);
_evaluationDataLogger = evaluationDataLogger ??
ExperimentUtils.ReadDataLogger(xmlConfig, LoggingType.Evaluation);
}
public override void Initialize(ExperimentDictionary experimentDictionary)
{
base.Initialize(experimentDictionary);
// Ensure the start position and minimum distance constraint are not null
Debug.Assert(experimentDictionary.Primary_MCS_MinimalCriteriaStartX != null,
"experimentDictionary.Primary_MCS_MinimalCriteriaStartX != null");
Debug.Assert(experimentDictionary.Primary_MCS_MinimalCriteriaStartY != null,
"experimentDictionary.Primary_MCS_MinimalCriteriaStartY != null");
Debug.Assert(experimentDictionary.Primary_MCS_MinimalCriteriaThreshold != null,
"experimentDictionary.Primary_MCS_MinimalCriteriaThreshold != null");
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(
experimentDictionary, true);
// Read in steady-state specific parameters
_batchSize = experimentDictionary.Primary_OffspringBatchSize ?? default(int);
_populationEvaluationFrequency = experimentDictionary.Primary_PopulationEvaluationFrequency ?? default(int);
// Read in MCS selection method
_mcsSelectionMethod = experimentDictionary.Primary_SelectionAlgorithmName;
// Read in log file path/name
_evolutionDataLogger = new NoveltyExperimentEvaluationEntityDataLogger(experimentDictionary.ExperimentName);
_evaluationDataLogger =
new NoveltyExperimentOrganismStateEntityDataLogger(experimentDictionary.ExperimentName);
}
public override void Initialize(ExperimentDictionary experimentDictionary)
{
base.Initialize(experimentDictionary);
// Read in behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(
experimentDictionary, true);
// Read in novelty archive parameters
_archiveAdditionThreshold = experimentDictionary.Primary_NoveltySearch_ArchiveAdditionThreshold ??
default(int);
_archiveThresholdDecreaseMultiplier =
experimentDictionary.Primary_NoveltySearch_ArchiveThresholdDecreaseMultiplier ?? default(double);
_archiveThresholdIncreaseMultiplier =
experimentDictionary.Primary_NoveltySearch_ArchiveThresholdIncreaseMultiplier ?? default(double);
_maxGenerationArchiveAddition =
experimentDictionary.Primary_NoveltySearch_MaxGenerationsWithArchiveAddition ?? default(int);
_maxGenerationsWithoutArchiveAddition =
experimentDictionary.Primary_NoveltySearch_MaxGenerationsWithoutArchiveAddition ?? default(int);
// Read in nearest neighbors for behavior distance calculations
_nearestNeighbors = experimentDictionary.Primary_NoveltySearch_NearestNeighbors ?? default(int);
// Read in steady-state specific parameters
_batchSize = experimentDictionary.Primary_OffspringBatchSize ?? default(int);
_populationEvaluationFrequency = experimentDictionary.Primary_PopulationEvaluationFrequency ?? default(int);
}
public override void Initialize(ExperimentDictionary experimentDictionary)
{
base.Initialize(experimentDictionary);
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(
experimentDictionary, true);
// Read in number of offspring to produce in a single batch
_batchSize = experimentDictionary.Primary_OffspringBatchSize ?? default(int);
// Read in the bridging magnitude
_bridgingMagnitude = experimentDictionary.Primary_MCS_BridgingMagnitude ?? default(int);
_bridgingApplications = experimentDictionary.Primary_MCS_BridgingApplications ?? default(int);
// TODO: Read seed genome count from the database
// Read in log file path/name
_evolutionDataLogger = new McsExperimentEvaluationEntityDataLogger(experimentDictionary.ExperimentName);
_evaluationDataLogger =
new McsExperimentOrganismStateEntityDataLogger(experimentDictionary.ExperimentName);
// Initialize the initialization algorithm
_mazeNavigationInitializer = new NoveltySearchMazeNavigationInitializer(MaxEvaluations, _evolutionDataLogger,
_evaluationDataLogger,
SerializeGenomeToXml);
// Setup initialization algorithm
_mazeNavigationInitializer.SetAlgorithmParameters(experimentDictionary, InputCount, OutputCount);
// Pass in maze experiment specific parameters
_mazeNavigationInitializer.SetEnvironmentParameters(MaxDistanceToTarget, MaxTimesteps, MazeVariant,
MinSuccessDistance);
}
/// <summary>
/// Constructs and initializes the MCS initialization algorithm (novelty search) using the database configuration.
/// </summary>
/// <param name="experimentDictionary">The reference to the experiment dictionary entity.</param>
/// <param name="inputCount">The number of input neurons.</param>
/// <param name="outputCount">The number of output neurons.</param>
/// <returns>The constructed initialization algorithm.</returns>
public void SetAlgorithmParameters(ExperimentDictionary experimentDictionary, int inputCount,
int outputCount)
{
// Read NEAT parameters
NeatGenomeParameters neatGenomeParameters =
ExperimentUtils.ReadNeatGenomeParameters(experimentDictionary, false);
// Read NEAT evolution parameters
NeatEvolutionAlgorithmParameters =
ExperimentUtils.ReadNeatEvolutionAlgorithmParameters(experimentDictionary, false);
// Get complexity constraint parameters
ComplexityRegulationStrategyDefinition =
experimentDictionary.Initialization_ComplexityRegulationStrategy;
ComplexityThreshold = experimentDictionary.Initialization_ComplexityThreshold;
// Read in the behavior characterization
_behaviorCharacterizationFactory =
ExperimentUtils.ReadBehaviorCharacterizationFactory(experimentDictionary, false);
// Read in the novelty archive parameters
_archiveAdditionThreshold =
experimentDictionary.Initialization_NoveltySearch_ArchiveAdditionThreshold ?? default(double);
_archiveThresholdDecreaseMultiplier =
experimentDictionary.Initialization_NoveltySearch_ArchiveThresholdDecreaseMultiplier ??
default(double);
_archiveThresholdIncreaseMultiplier =
experimentDictionary.Initialization_NoveltySearch_ArchiveThresholdIncreaseMultiplier ??
default(double);
_maxGenerationArchiveAddition =
experimentDictionary.Initialization_NoveltySearch_MaxGenerationsWithArchiveAddition ??
default(int);
_maxGenerationsWithoutArchiveAddition =
experimentDictionary.Initialization_NoveltySearch_MaxGenerationsWithoutArchiveAddition ??
default(int);
// Read in nearest neighbors for behavior distance calculations
_nearestNeighbors = experimentDictionary.Initialization_NoveltySearch_NearestNeighbors ?? default(int);
// Read in steady-state specific parameters
_batchSize = experimentDictionary.Initialization_OffspringBatchSize ?? default(int);
_populationEvaluationFrequency = experimentDictionary.Initialization_PopulationEvaluationFrequency ??
default(int);
}
/// <summary>
/// Constructs and initializes the MCS initialization algorithm (novelty search).
/// </summary>
/// <param name="xmlConfig">The XML configuration for the initialization algorithm.</param>
/// <param name="inputCount">The number of input neurons.</param>
/// <param name="outputCount">The number of output neurons.</param>
/// <returns>The constructed initialization algorithm.</returns>
public override void SetAlgorithmParameters(XmlElement xmlConfig, int inputCount, int outputCount)
{
// Set the boiler plate parameters
base.SetAlgorithmParameters(xmlConfig, inputCount, outputCount);
// Read the target population size
PopulationSize = XmlUtils.GetValueAsInt(xmlConfig, "PopulationSize");
// 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");
}
public override void Initialize(string name, XmlElement xmlConfig, IDataLogger evolutionDataLogger,
IDataLogger evaluationDataLogger)
{
base.Initialize(name, xmlConfig, evolutionDataLogger, evaluationDataLogger);
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(xmlConfig,
"BehaviorConfig");
// 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");
// Read in log file path/name
_generationalLogFile = XmlUtils.TryGetValueAsString(xmlConfig, "GenerationalLogFile");
}
public override void Initialize(string name, XmlElement xmlConfig, IDataLogger evolutionDataLogger,
IDataLogger evaluationDataLogger)
{
base.Initialize(name, xmlConfig, evolutionDataLogger, evaluationDataLogger);
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(xmlConfig,
"BehaviorConfig");
// Read in number of offspring to produce in a single batch
_batchSize = XmlUtils.GetValueAsInt(xmlConfig, "OffspringBatchSize");
// Read in the bridging magnitude and number of applications
_bridgingMagnitude = XmlUtils.TryGetValueAsInt(xmlConfig, "BridgingMagnitude") ?? default(int);
_bridgingApplications = XmlUtils.TryGetValueAsInt(xmlConfig, "BridgingApplications") ?? default(int);
// Read in the number of seed genomes to generate to bootstrap the primary algorithm
SeedGenomeCount = XmlUtils.GetValueAsInt(xmlConfig, "SeedGenomeCount");
// Read in log file path/name
_evolutionDataLogger = evolutionDataLogger ??
ExperimentUtils.ReadDataLogger(xmlConfig, LoggingType.Evolution);
_evaluationDataLogger = evaluationDataLogger ??
ExperimentUtils.ReadDataLogger(xmlConfig, LoggingType.Evaluation);
// Setup the specific logging options based on parameters that are enabled/disabled
_experimentLogFieldEnableMap = EvolutionFieldElements.PopulateEvolutionFieldElementsEnableMap();
// Enable or disable genome XML logging
if (SerializeGenomeToXml == false)
{
_experimentLogFieldEnableMap.Add(EvolutionFieldElements.ChampGenomeXml, false);
}
// Enable or disable primary fitness logging (causing utilization of auxiliary fitness)
if (_bridgingMagnitude > 0)
{
_experimentLogFieldEnableMap.Add(EvolutionFieldElements.ChampGenomeFitness, false);
}
// Initialize the initialization algorithm
_mazeNavigationInitializer = new NoveltySearchMazeNavigationInitializer(MaxEvaluations, _evolutionDataLogger,
_evaluationDataLogger,
SerializeGenomeToXml);
// Setup initialization algorithm
_mazeNavigationInitializer.SetAlgorithmParameters(
xmlConfig.GetElementsByTagName("InitializationAlgorithmConfig", "")[0] as XmlElement, InputCount,
OutputCount);
// Pass in maze experiment specific parameters
_mazeNavigationInitializer.SetEnvironmentParameters(MaxDistanceToTarget, MaxTimesteps, MazeVariant,
MinSuccessDistance);
}
/// <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;
}
public override void Initialize(string name, XmlElement xmlConfig, IDataLogger evolutionDataLogger,
IDataLogger evaluationDataLogger)
{
base.Initialize(name, xmlConfig, evolutionDataLogger, evaluationDataLogger);
// Read in the behavior characterization
_behaviorCharacterizationFactory = ExperimentUtils.ReadBehaviorCharacterizationFactory(xmlConfig,
"BehaviorConfig");
// Read in the novelty archive parameters
// 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");
}
