public AIInstance(InstanceSelector instanceSelector, int instanceNumber, Queue decisionRequestQueue, AIRandomControl aiRandomControl)
{
taskTrees = new Dictionary <RequestedInfoKey, InfoProviderTaskTree>();
this.instanceSelector = instanceSelector;
this.instanceNumber = instanceNumber;
this.decisionRequestQueue = decisionRequestQueue;
this.decisionInProgress = new object();
//Setup the AI's and providers here
infoStore = new InfoCollection();
infoProviderDictList = new Dictionary <InfoProviderType, InfoProviderBase>();
aiDictList = new Dictionary <AIGeneration, AIBase>();
//Setup the 1st infostore instance
var GP = new GameProvider(infoStore, infoProviderDictList, aiRandomControl);
var WRP = new ProviderWinRatio.WinRatioProvider(infoStore, infoProviderDictList, aiRandomControl);
var BP = new BetsProvider(infoStore, infoProviderDictList, aiRandomControl);
var CP = new CardsProvider(infoStore, infoProviderDictList, aiRandomControl);
var AP = new AggressionProvider(infoStore, infoProviderDictList, aiRandomControl);
var PAPP = new PlayerActionPredictionProvider(infoStore, infoProviderDictList, aiRandomControl);
//Hard lock the infostore collection preventing any further changes.
infoStore.HardLockInfoList();
//Setup the AI list
//We are going to lock the AI's into random mode.
aiDictList.Add(AIGeneration.SimpleV1, new SimpleAIV1(aiRandomControl));
aiDictList.Add(AIGeneration.SimpleV2, new SimpleAIV2(aiRandomControl));
aiDictList.Add(AIGeneration.NeuralV1, new NeuralAIv1(aiRandomControl));
aiDictList.Add(AIGeneration.SimpleV3, new SimpleAIV3(aiRandomControl));
aiDictList.Add(AIGeneration.NeuralV2, new NeuralAIv2(aiRandomControl));
aiDictList.Add(AIGeneration.SimpleV4AggressionTrack, new SimpleAIV4AggTrack(aiRandomControl));
aiDictList.Add(AIGeneration.NeuralV3, new NeuralAIv3(aiRandomControl));
aiDictList.Add(AIGeneration.NeuralV4, new NeuralAIv4(aiRandomControl));
aiDictList.Add(AIGeneration.SimpleV5, new SimpleAIv5(aiRandomControl));
aiDictList.Add(AIGeneration.SimpleV6, new SimpleAIv6(aiRandomControl));
aiDictList.Add(AIGeneration.NeuralV5, new NeuralAIv5(aiRandomControl));
aiDictList.Add(AIGeneration.NeuralV6, new NeuralAIv6(aiRandomControl));
aiDictList.Add(AIGeneration.SimpleV7, new SimpleAIv7(aiRandomControl));
aiDictList.Add(AIGeneration.CheatV1, new CheatV1(aiRandomControl));
aiDictList.Add(AIGeneration.NeuralV7, new NeuralAIv7(aiRandomControl));
if (ConcurrencyMode.Concurrency == ConcurrencyMode.ConcurencyModel.MultiCore)
{
providerTasks = new Dictionary <InfoProviderType, Task>();
}
else
{
providerActions = new Dictionary <InfoProviderType, Action>();
}
}
protected void InitTargets()
{
int length = TargetLength;
Targets = new List <InstanceSelector>(length);
For
(length, (i) =>
{
var newSelector = new InstanceSelector
(TargetObjects[i], TargetNames[i]);
Targets.Add(newSelector);
});
}
private void AIManagerConstructor(int numInstances, AIRandomControl aiRandomControl, bool runInSafeMode, Object jobToRun)
{
RunInSafeMode = runInSafeMode;
InfoProviderBase.CurrentJob = jobToRun;
this.decisionRequestQueue = new Queue();
instanceSelector = new InstanceSelector();
aiInstanceList = new List <AIInstance>();
//Setup the instances
for (int i = 0; i < numInstances; i++)
{
aiInstanceList.Add(new AIInstance(instanceSelector, i, decisionRequestQueue, aiRandomControl));
}
for (int i = 0; i < numInstances; i++)
{
instanceSelector.instancesIdle = instanceSelector.instancesIdle | (1 << i);
}
}
/// <summary>
/// Initializes a new instance of the <see cref="AlgorithmTuner{TTargetAlgorithm,TInstance,TResult,TModelLearner,TPredictorModel,TSamplingStrategy}"/> class.
/// </summary>
/// <param name="targetAlgorithmFactory">
/// Produces configured instances of the algorithm to tune.
/// </param>
/// <param name="runEvaluator">
/// Object for evaluating target algorithm runs.
/// </param>
/// <param name="trainingInstances">
/// The set of instances used for tuning.
/// </param>
/// <param name="parameterTree">
/// Provides the tunable parameters.
/// </param>
/// <param name="configuration">
/// Algorithm tuner configuration parameters.
/// </param>
/// <param name="genomeBuilder">
/// Responsible for creation, modification and crossover of genomes.
/// Needs to be compatible with the given parameter tree and configuration.
/// This parameter can be left out if an ordinary <see cref="GenomeBuilder"/> should be used.
/// </param>
public AlgorithmTuner(
ITargetAlgorithmFactory <TTargetAlgorithm, TInstance, TResult> targetAlgorithmFactory,
IRunEvaluator <TResult> runEvaluator,
IEnumerable <TInstance> trainingInstances,
ParameterTree parameterTree,
AlgorithmTunerConfiguration configuration,
GenomeBuilder genomeBuilder)
{
ValidateParameters(targetAlgorithmFactory, runEvaluator, trainingInstances, parameterTree, configuration, genomeBuilder);
LoggingHelper.WriteLine(
VerbosityLevel.Info,
$"Tuning target algorithm with {parameterTree.GetParameters().Count()} parameters.");
this._configuration = configuration;
this._runEvaluator = runEvaluator;
this.GeneticEngineering = new GeneticEngineering <TModelLearner, TPredictorModel, TSamplingStrategy>(parameterTree, this._configuration);
this.IncumbentQuality = new List <double>();
this._trainingInstances = trainingInstances.ToList();
this._instanceSelector = new InstanceSelector <TInstance>(this._trainingInstances, configuration);
this._parameterTree = parameterTree;
this._genomeBuilder = genomeBuilder;
this._targetAlgorithmRunActors = ActorSystem.Create(AkkaNames.ActorSystemName, configuration.AkkaConfiguration);
this._targetRunResultStorage = this._targetAlgorithmRunActors.ActorOf(
Props.Create(() => new ResultStorageActor <TInstance, TResult>()),
AkkaNames.ResultStorageActor);
this._genomeSorter = this._targetAlgorithmRunActors.ActorOf(
Props.Create(() => new GenomeSorter <TInstance, TResult>(runEvaluator)),
AkkaNames.GenomeSorter);
this._logWriter = new LogWriter <TInstance, TResult>(parameterTree, configuration);
this._populationUpdateStrategyManager = new PopulationUpdateStrategyManager <TInstance, TResult>(
this.CreatePopulationUpdateStrategies(targetAlgorithmFactory, runEvaluator).ToList(),
configuration);
}
