exp-examples.mini-robot-vs-nav.txt Maven / Gradle / Ivy

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Experimenter tool based on jgea and textual config files (with jnb).
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$descBehav1 = ds.e.n.x(of = ds.e.n.finalRobotP(of = ea.f.simOutcome(of = ea.f.quality())))
$descBehav2 = ds.e.n.y(of = ds.e.n.finalRobotP(of = ea.f.simOutcome(of = ea.f.quality())))
$descBody1 = f.avg(of = f.pairFirst(of = ea.f.genotype()))
$descBody2 = f.sd(of = f.pairFirst(of = ea.f.genotype()))
$descBrainSize1 = ea.f.treeSize(of = f.nTh(of = f.pairSecond(of = ea.f.genotype()); n = 0))
$descBrainSize2 = ea.f.treeSize(of = f.nTh(of = f.pairSecond(of = ea.f.genotype()); n = 1))
$descBrainUsage1 = f.mathOp(of = f.pairSecond(of = ea.f.genotype()); op = add; args = [
  ea.f.treeSize(of = f.nTh(n = 0));
  ea.f.treeSize(of = f.nTh(n = 1))
])
$descBrainUsage2 = f.mathOp(of = f.pairSecond(of = ea.f.genotype()); op = add; args = [
  f.size(of = f.filter(of = f.distinct(of = ea.f.treeLeaves(of = f.nTh(n = 0))); condition = predicate.matches(f = f.toString(); regex = "i[0-9]+")));
  f.size(of = f.filter(of = f.distinct(of = ea.f.treeLeaves(of = f.nTh(n = 1))); condition = predicate.matches(f = f.toString(); regex = "i[0-9]+")))
])

ea.experiment(
  runs = (randomGenerator = (seed = [1:1:1]) * [m.defaultRG()]) *
  (solver = (nEval = [1000]) *
  (mapper = [ea.mapper.pair(second = ea.mapper.nmrfToNds(of = ea.mapper.multiSrTreeToNmrf()))])
  * [
    ea.s.ga(
      representation = ea.representation.pair(first = ea.representation.doubleString(); second = ea.representation.multiSRTree())
    );
    ea.s.mapElites(
      name = "me2-pos";
      representation = ea.representation.pair(first = ea.representation.doubleString(); second = ea.representation.multiSRTree());
      descriptors = [
        ea.s.me.d.descriptor(f = $descBehav1; min = 0; max = 1; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBehav2; min = 0; max = 1; nOfBins = 10)
      ]
    );
    ea.s.mapElites(
      name = "me2-body";
      representation = ea.representation.pair(first = ea.representation.doubleString(); second = ea.representation.multiSRTree());
      descriptors = [
        ea.s.me.d.descriptor(f = $descBody1; min = -1.57; max = 1.57; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBody2; min = 0; max = 3.14; nOfBins = 10)
      ]
    );
    ea.s.mapElites(
      name = "me2-brain-sizes";
      representation = ea.representation.pair(first = ea.representation.doubleString(); second = ea.representation.multiSRTree());
      descriptors = [
        ea.s.me.d.descriptor(f = $descBrainSize1; min = 10; max = 410; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBrainSize2; min = 10; max = 410; nOfBins = 10)
      ]
    );
    ea.s.mapElites(
      name = "me2-brain-size-usage";
      representation = ea.representation.pair(first = ea.representation.doubleString(); second = ea.representation.multiSRTree());
      descriptors = [
        ea.s.me.d.descriptor(f = $descBrainUsage1; min = 0; max = 500; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBrainUsage2; min = 0; max = 20; nOfBins = 10)
      ]
    );
    ea.s.mapElites(
      name = "me4-body+brain-sizes";
      representation = ea.representation.pair(first = ea.representation.doubleString(); second = ea.representation.multiSRTree());
      descriptors = [
        ea.s.me.d.descriptor(f = $descBody1; min = -1.57; max = 1.57; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBody2; min = 0; max = 3.14; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBrainSize1; min = 10; max = 410; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBrainSize2; min = 10; max = 410; nOfBins = 10)
      ]
    );
    ea.s.mapElites(
      name = "me4-body+brain-size-usage";
      representation = ea.representation.pair(first = ea.representation.doubleString(); second = ea.representation.multiSRTree());
      descriptors = [
        ea.s.me.d.descriptor(f = $descBody1; min = -1.57; max = 1.57; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBody2; min = 0; max = 3.14; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBrainUsage1; min = 0; max = 500; nOfBins = 10);
        ea.s.me.d.descriptor(f = $descBrainUsage2; min = 0; max = 20; nOfBins = 10)
      ]
    )
  ]) *
  [ea.run(
    problem = ea.p.simTo(
      simulation = ds.s.variableSensorPositionsNavigation(arena = e_maze; nOfSensors = 9; finalT = 30);
      f = ds.e.n.finalD();
      type = minimize
    )
  )];
  listeners = [
    ea.l.console(
      functions = [
        ea.f.simQuality(of = ea.f.quality(of = ea.f.best()); format = "%9.5f");
        ea.f.archiveCoverage(of = ea.f.meArchive())
      ];
      onlyLast = true
    );
    ea.l.savePlotForRun(
      plot = ea.plot.multi.quality(q = ea.f.simQuality());
      path = "../fitness-part"
    );
    ea.l.savePlotForExp(
      plot = ea.plot.multi.quality(q = ea.f.simQuality());
      path = "../fitness"
    );
    ea.l.saveForRun(
      of = ea.acc.lastBest();
      path = "../best-traj-{run.index:%04d}";
      processor = ea.f.toImage(image = ds.d.navigation(); of = ea.f.simOutcome(of = ea.f.quality()))
    );
    ea.l.saveLastPopulationForRun(
      path = "../run-{run.index:%04d}-last-pop"
    )
  ]
)