protected override void EvaluateObjective(TuringController controller, int iterations, ref EvaluationInfo evaluation)
{
Utility.Debug.DLogHeader("STARTING EVAULATION", true);
double totalScore = 0;
// Iteration loop
for (int i = 0; i < iterations; i++)
{
Utility.Debug.DLogHeader($"EVALUATION ITERATION {i}", true);
Reset();
double[] enviromentOutput = Environment.InitialObservation;
// Environment loop
while (!Environment.IsTerminated)
{
// Activate the controller with the environment output.
// The turing controller will handle the turing machine I/O
double[] environmentInput = controller.ActivateNeuralNetwork(enviromentOutput);
// Activate the environment with the output from the controller (NN)
enviromentOutput = Environment.PerformAction(environmentInput);
}
totalScore += Environment.NormalizedScore;
Utility.Debug.DLog($"EVALUATION Total Score: {totalScore}, Iteration Score: {Environment.CurrentScore}", true);
}
// Calculate the total normalized score (0-1)
evaluation.ObjectiveFitness = Math.Max(0d, totalScore / iterations);
}
protected override void EvaluateObjective(TuringController controller, int iterations, ref EvaluationInfo evaluation)
{
Utility.Debug.DLogHeader("STARTING EVAULATION", true);
double totalScore = 0;
evaluation.TapeSizes = new int[iterations];
// Iteration loop
for (int i = 0; i < iterations; i++)
{
Utility.Debug.DLogHeader($"EVALUATION ITERATION {i}", true);
Reset();
double[] enviromentOutput = Environment.InitialObservation;
// Environment loop
while (!Environment.IsTerminated)
{
// Activate the controller with the environment output.
// The turing controller will handle the turing machine I/O
double[] environmentInput = controller.ActivateNeuralNetwork(enviromentOutput);
if (_turingMachineProps.MemorySizeHardLimit > 0 &&
controller.TuringMachine.TapeSize > _turingMachineProps.MemorySizeHardLimit)
{
evaluation.ObjectiveFitness = 0d;
// Phenome is disqualified, no need to do any further evaluation.
return;
}
// Activate the environment with the output from the controller (NN)
enviromentOutput = Environment.PerformAction(environmentInput);
}
totalScore += Environment.NormalizedScore;
evaluation.TapeSizes[i] = controller.TuringMachine.TapeSize;
Utility.Debug.DLog($"EVALUATION Total Score: {totalScore}, Iteration Score: {Environment.CurrentScore}", true);
}
// Calculate the total normalized score (0-1)
evaluation.ObjectiveFitness = Math.Max(0d, totalScore / iterations);
}
protected override void EvaluateRecord(TuringController controller, int iterations, ref EvaluationInfo evaluation)
{
// Iteration loop
for (int i = 0; i < iterations; i++)
{
Reset();
// Only record first iteration, as subsequent ones will overwrite
if (i == 0)
{
Recorder = new Recorder();
Recorder.Start();
controller.TuringMachine.RecordTimeSteps = true;
Environment.RecordTimeSteps = true;
Recorder.Record(Environment.InitialTimeStep, controller.TuringMachine.InitialTimeStep);
}
double[] enviromentOutput = Environment.InitialObservation;
// Environment loop
while (!Environment.IsTerminated)
{
double[] environmentInput = controller.ActivateNeuralNetwork(enviromentOutput);
enviromentOutput = Environment.PerformAction(environmentInput);
if (i == 0)
{
// Record the state of the environment and turing machine
Recorder.Record(Environment.PreviousTimeStep, controller.TuringMachine.PreviousTimeStep);
}
}
evaluation.ObjectiveFitnessIt[i] = Environment.NormalizedScore;
if (i == 0)
{
// Record the final state of the turing machine tape
Recorder.FinalTuringTape = Controller.TuringMachine.TapeValues;
}
}
}
protected override void EvaluateNovelty(TuringController controller, ref EvaluationInfo evaluation)
{
Reset();
double[] enviromentOutput = Environment.InitialObservation;
// Environment loop
while (!Environment.IsTerminated)
{
// Activate the controller with the environment output.
// The turing controller will handle the turing machine I/O
double[] environmentInput = controller.ActivateNeuralNetwork(enviromentOutput);
// Activate the environment with the output from the controller (NN)
enviromentOutput = Environment.PerformAction(environmentInput);
}
evaluation.NoveltyVectors = NoveltySearchInfo.NoveltyVectors;
evaluation.MinimumCriteria = NoveltySearchInfo.MinimumCriteria;
}