options.setPauseWorld(false);
Evolvable initial = new SmallMLPAgent();
RegisterableAgent.registerAgent ((Agent) initial);
options.setMaxFPS(true);
options.setVisualization(false);
MultiDifficultyProgressTask task = new MultiDifficultyProgressTask(options);
ES es = new ES (task, initial, populationSize);
System.out.println("Evolving " + initial + " with task " + task);
final String fileName = "evolved" + (int) (Math.random () * Integer.MAX_VALUE) + ".xml";
for (int gen = 0; gen < generations; gen++) {
task.setStartingSeed((int) (Math.random () * Integer.MAX_VALUE));
es.nextGeneration();
double bestResult = es.getBestFitnesses()[0];
System.out.println("Generation " + gen + " best " + bestResult);
Evolvable bestEvolvable = es.getBests()[0];
double[] fitnesses = task.evaluate((Agent) bestEvolvable);
System.out.printf("%.4f %.4f %.4f %.4f %.4f\n",
fitnesses[0], fitnesses[1], fitnesses[2], fitnesses[3], fitnesses[4]);
Easy.save (es.getBests()[0], fileName);
}
Stats.main(new String[]{fileName, "0"});