StatisticalSummary ss = new StatisticalSummary ();
for (int i = 0; i < numberOfTrials; i++) {
options.setLevelRandSeed(seed + i);
controller.reset();
options.setAgent(controller);
Evaluator evaluator = new Evaluator (options);
EvaluationInfo result = evaluator.evaluate().get(0);
System.out.printf(" map seed %d diff %2d -> %f (%f ms/frame)\n", seed+i, level, result.computeDistancePassed(), controller.averageTimeTaken());
ss.add (result.computeDistancePassed());
}
return ss;
}