public void TestEvolution()
{
Profiler.Reset();
var random = new SystemRandom(42);
var configuration = new ZeldaConfiguration(random);
var factory = new ZeldaGenomeFactory(configuration);
var initialVariables = new VariableAssignment();
var environment = new ZeldaEnvironment(new[] { initialVariables }, 10000);
var writer = File.CreateText("stats.csv");
var evolution = new ElitistEvolution(200, 100, factory, environment, ZeldaIndividual.NumAttributes, writer);
var genomes = evolution.Initialize();
// TODO Jonas: replace fixed weight multirank optimization by dynamic randomized weighting
// i.e. in some generations prefer some attribute over others
// evolve
for (int i = 0; i < 1000; i++)
{
Profiler.BeginFrame();
Console.WriteLine("gen " + i);
genomes = evolution.Evolve(genomes, random);
Profiler.EndFrame();
}
writer.Close();
var best = (ZeldaIndividual)evolution.GetBest(new TestComparer());
Console.WriteLine(best);
var crawler = best.Crawler;
var builder = new DotBuilder();
crawler.Express(builder);
// TODO: output genome to puzzle unit test (puzzle building statements)
Profiler.ExportToUnityProfileAnalyzer("w:\\EvolutionTest-TestEvolution.pdata");
}
public void CreateIndividual()
{
Profiler.Reset();
Profiler.BeginFrame();
var random = new SystemRandom(42);
var configuration = new ZeldaConfiguration(random);
var factory = new ZeldaGenomeFactory(configuration);
var initialVariables = new VariableAssignment();
var environment = new ZeldaEnvironment(new[] { initialVariables }, 10000);
var example = factory.CreateGenome();
var individual = environment.Evaluate(example);
Console.WriteLine("test: " + individual);
Profiler.EndFrame();
Profiler.ExportToUnityProfileAnalyzer("w:\\EvolutionTest-CreateIndividual.pdata");
}
