public void RunTrials(int numberOfTrials)
{
var visualArrayLength = 7; //state and action size are the size of the array in this case
var learning = new QLearningImplementation(0, 0, visualArrayLength, 6);
var trainingTrialRunner = new QLearningTrialRunner(_observableModel, _randomNumberProvider,
fixationLocation => new QLearningActor(learning, _observableModel, fixationLocation));
var testingTrialRunner = new QLearningTrialRunner(_observableModel, _randomNumberProvider,
fixationLocation =>
new QLearningTestActor(learning, _observableModel, fixationLocation, _cumulativeDataRepository));
var count = 0;
while (count < numberOfTrials)
{
trainingTrialRunner.Run(learning);
count++;
if (count%150 == 0 && count != 0)
{
testingTrialRunner.Run(learning);
_cumulativeDataRepository.IncrementTrial(count);
}
}
}
public void RunTrials(int trialsToLearn, int trialsToAnalyse)
{
var visualArrayLength = 7; //state and action size are the size of the array in this case
var learning = new QLearningImplementation(0, 0, visualArrayLength, 6);
var trainingTrialRunner = new QLearningTrialRunner(_observableModel, _randomNumberProvider,
fixationLocation => new QLearningActor(learning, _observableModel, fixationLocation));
var recordingTrialRunner = new QLearningRecordingTrialRunner(_observableModel, _randomNumberProvider,
fixationLocation => new QLearningActor(learning, _observableModel, fixationLocation), _dataRepository);
var learningCount = 0;
while (learningCount < trialsToLearn)
{
trainingTrialRunner.Run(learning);
learningCount++;
}
var analysisCount = 0;
while (analysisCount < trialsToAnalyse)
{
recordingTrialRunner.Run(learning);
analysisCount++;
}
}