public static NeatEvolutionAlgorithm <double> CreateNeatEvolutionAlgorithm(
INeatExperimentFactory <double> experimentFactory,
string jsonConfigFilename)
{
// Load experiment json config from file.
JsonDocument configDoc = JsonUtils.LoadUtf8(jsonConfigFilename);
// Create an instance of INeatExperiment, configured using the supplied json config.
INeatExperiment <double> neatExperiment = experimentFactory.CreateExperiment(configDoc.RootElement);
// Create a NeatEvolutionAlgorithm instance ready to run the experiment.
var ea = NeatExperimentUtils.CreateNeatEvolutionAlgorithm(neatExperiment);
return(ea);
}
public static NeatEvolutionAlgorithm <double> CreateNeatEvolutionAlgorithm(
INeatExperimentFactory <double> experimentFactory,
string jsonConfigFilename)
{
// Read experiment json config from file.
// Note. We read the entire contents into a string; we don't ever expect to see large json files here, so this fine.
string jsonStr = File.ReadAllText(jsonConfigFilename);
// Create an instance of INeatExperiment, configured using the supplied json config.
INeatExperiment <double> neatExperiment = experimentFactory.CreateExperiment(jsonStr);
// Create a NeatEvolutionAlgorithm instance ready to run the experiment.
var ea = NeatExperimentUtils.CreateNeatEvolutionAlgorithm(neatExperiment);
return(ea);
}
/// <summary>
/// Initialise and run the evolutionary algorithm until the stop condition occurs (either elapsed clock time, or some number of generations).
/// Once the stop condition is reached this method returns with the current best fitness in the population.
/// </summary>
/// <returns></returns>
public Sample Sample()
{
// Create a new instance of an evolution algorithm.
NeatEvolutionAlgorithm <double> ea = NeatExperimentUtils.CreateNeatEvolutionAlgorithm(_experiment);
// Start the stopwatch.
_stopwatch.Restart();
// We include clock time spent doing initialisation in the recorded stats for each sample;
// this is the scientifically robust approach as initialisation might perform a lot of work.
ea.Initialise();
// Run the main EA loop for the required number of generations.
for (int i = 0; i < _stopGenerationCount; i++)
{
ea.PerformOneGeneration();
}
// Stop the stopwatch.
_stopwatch.Stop();
// Copy the required stats into a new Sample instance.
Sample sample = new Sample();
sample.ElapsedTimeSecs = _stopwatch.ElapsedMilliseconds * 0.001;
sample.GenerationCount = (int)ea.Stats.Generation;
var pop = ea.Population;
sample.BestFitness = pop.Stats.BestFitness.PrimaryFitness;
sample.MeanFitness = pop.Stats.MeanFitness;
// TODO: Store max complexity? Or should we use BestComplexity? Or both?
//sample.MaxComplexity = ;
sample.MeanComplexity = pop.Stats.MeanComplexity;
sample.EvaluationCount = ea.Stats.TotalEvaluationCount;
// Make some attempts at forcing release of resources (especially RAM) before we hand control back.
ea = null;
GC.Collect(GC.MaxGeneration, GCCollectionMode.Forced, true);
// Return the sample.
return(sample);
}
/// <summary>
/// Initialise and run the evolutionary algorithm until the stop condition occurs (either elapsed clock time, or some number of generations).
/// Once the stop condition is reached this method returns with the current best fitness in the population.
/// </summary>
/// <returns></returns>
public Sample Sample()
{
// Create a new instance of an evolution algorithm.
_ea = NeatExperimentUtils.CreateNeatEvolutionAlgorithm(_experiment);
// Start the stopwatch.
_stopwatch.Restart();
// Signal the EA thread to start. Ensure the stop flag is reset before we do so.
_stopFlag = false;
Thread.MemoryBarrier();
_awaitStartEvent.Set();
// Block this thread (the main thread) for the required amount of clock time.
Block(_stopTimeSpan);
// Signal the EA thread to stop.
_stopFlag = true;
Thread.MemoryBarrier();
// Record the sample without waiting for the EA to stop.
// The EA may be within a PerformOneGeneration() call for some time, so we prefer to record the sample
// at the exact required point in time (or very close to it) rather than some arbitrary point in time
// after the last generation has completed.
Sample sample = RecordSample();
// Now wait for the EA to signal that it has stopped.
_awaitStopEvent.WaitOne();
// Make some attempts at forcing release of resources (especially RAM) before we hand control back.
_ea = null;
GC.Collect(GC.MaxGeneration, GCCollectionMode.Forced, true);
// Return the sample.
return(sample);
}